Cyclical Features of Uzawa-Lucas Endogenous Growth Model

This paper analyzes the cyclical properties of a generalized version of Uzawa-Lucas endogenous growth model. We study the dynamic features of different cyclical components of this model characterized by a variety of decomposition methods. The decomposition methods considered can be classified in two groups. On the one hand, we consider three statistical filters: the Hodrick-Prescott filter, the Baxter-King filter and Gonzalo-Granger decomposition. On the other hand, we use four model-based decomposition methods. The latter decomposition procedures share the property that the cyclical components obtained by these methods preserve the log-linear approximation of the Euler-equation restrictions imposed by the agent’s intertemporal optimization problem. The paper shows that both model dynamics and model performance substantially vary across decomposition methods. A parallel exercise is carried out with a standard real business cycle model. The results should help researchers to better understand the performance of Uzawa-Lucas model in relation to standard business cycle models under alternative definitions of the business cycle.

SNP Discovery in European Anchovy (Engraulis encrasicolus, L) by High-Throughput Transcriptome and Genome Sequencing

12 p.

Mitigation Techniques to Reduce the Impact of Wind Turbines on Radar Services

Radar services are occasionally affected by wind farms. This paper presents a comprehensive description of the effects that a wind farm may cause on the different radar services, and it compiles a review of the recent research results regarding the mitigation techniques to minimize this impact. Mitigation techniques to be applied at the wind farm and on the radar systems are described. The development of thorough impact studies before the wind farm is installed is presented as the best way to analyze in advance the potential for interference, and subsequently identify the possible solutions to allow the coexistence of wind farms and radar services.

Rhythm Analysis during Cardiopulmonary Resuscitation: Past, Present, and Future

Survival from out-of-hospital cardiac arrest depends largely on two factors: early cardiopulmonary resuscitation (CPR) and early defibrillation. CPR must be interrupted for a reliable automated rhythm analysis because chest compressions induce artifacts in the ECG. Unfortunately, interrupting CPR adversely affects survival. In the last twenty years, research has been focused on designing methods for analysis of ECG during chest compressions. Most approaches are based either on adaptive filters to remove the CPR artifact or on robust algorithms which directly diagnose the corrupted ECG. In general, all the methods report low specificity values when tested on short ECG segments, but how to evaluate the real impact on CPR delivery of continuous rhythm analysis during CPR is still unknown. Recently, researchers have proposed a new methodology to measure this impact. Moreover, new strategies for fast rhythm analysis during ventilation pauses or high-specificity algorithms have been reported. Our objective is to present a thorough review of the field as the starting point for these late developments and to underline the open questions and future lines of research to be explored in the following years.

Local and Global Externalities, Environmental Policies and Growth

33 p.

Diseño y evaluación de métodos de supresión del artefacto causado en el ECG por las compresiones torácicas proporcionadas por el dispositivo mecánico LUCAS.

[Es]En este proyecto se analizan el diseño y la evaluación de dos métodos para la supresión de la interferencia generada por las compresiones torácicas proporcionadas por el dispositivo mecánico LUCAS, en el electrocardiograma (ECG) durante el masaje de resucitación cardiopulmonar. El objetivo es encontrar un método que elimine el artefacto generado en el ECG de una manera efectiva, que permita el diagnóstico fiable del ritmo cardiaco. Encontrar un método eficaz sería de gran ayuda para no tener que interrumpir el masaje de resucitación para el análisis correcto del ritmo cardiaco, lo que supondría un aumento en las probabilidades de resucitación. Para llevar a cabo el proyecto se ha generado una base de datos propia partiendo de registros de paradas cardiorrespiratorias extra-hospitalarias. Esta nueva base de datos contiene 410 cortes correspondientes a 86 pacientes, siendo todos los episodios de 30 segundos de duración y durante los cuales el paciente, recibe masaje cardiaco. Por otro lado, se ha desarrollado una interfaz gráfica para caracterizar los métodos de supresión del artefacto. Esta, muestra las señales del ECG, de impedancia torácica y del ECG tras eliminar el artefacto en tiempo. Mediante esta herramienta se han procesado los registros aplicando un filtro adaptativo y un filtro de coeficientes constantes. La evaluación de los métodos se ha realizado en base a la sensibilidad y especificidad del algoritmo de clasificación de ritmos con las señales ECG filtradas. La mayor aportación del proyecto, por tanto, es el desarrollo de una potente herramienta eficaz para evaluar métodos de supresión del artefacto causado en el ECG por las compresiones torácicas al realizar el masaje de resucitación cardiopulmonar, y su posterior diagnóstico. Un instrumento que puede ser implementado para analizar episodios de resucitación de cualquier tipo de procedencia y capaz de integrar nuevos métodos de supresión del artefacto.