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The problem of the high carbon dioxide emissions linked to power generation makes necessary active research on the use of biofuels in gas turbine systems as a promising alternative to fossil fuels. Gasification of biomass waste is particularly of interest in obtaining a fuel to be run in gas turbines, as it is an efficient biomass-to-biofuel conversion process, and an integration into a combined cycle power plant leads to a high performance with regard to energetic efficiency. The goal of this study was to carry out an energetic, exergetic and environmental analysis of the behaviour of an integrated gasification combined cycle (IGCC) plant fuelled with different kinds of biomass waste by means of simulations. A preliminary economic study is also included. Although a technological development in gasification technology is necessary, the results of simulations indicate a high technical and environmental interest in the use of biomass integrated gasification combined cycle (BioIGCC) systems for large-scale power generation from biomass waste.

The early diagnosis of ischemic events may prevent irreversible damage to the heart muscle. Mobile IntroductionMyocardial ischemia is one of the diseases with highest incidence rate in the industrialised countries. Physiologically, is identified by an insufficient oxygenated blood supply compared to current myocardial demand. This event is reflected in a ECG signal as anomalous variations during the ventricular re-polarization. Although the ECG signal analysis is not the most accurate method that exists to detect the ischemic events, it is without question, the least invasive and costly one, and still maintain a high sensitivity level in the detection.Moreover, prolonged, severe or repeated ischemic episodes can lead to irreversible damages to the cardiac tissue. Therefore it comes up the importance of the early detection of such kind of episodes.The latest technological advances in the communication and mobile devices have led to significant progresses of the mobile computing area and give the possibility of new any time and anywhere telemonitoring solution. The combination of real time ischemia detection methods with mobile computing techniques may give the solution to the early detection of ischemic events through innovative telemonitoring systems.The aim of this paper is to present the structure and the validation results of a detection algorithm of transient ischemic events based on ECG signal analysis. The algorithm can be embedded in a mobile such as a PDA and can be executed in real time. Those requirements involve some rules that we had in mind during the development of the algorithm: 1. to be simple enough and with a low computation cost to fulfill the time restrictions of a real time execution in a device with limited computation capabilities and memory capacity (PDA); 2. to generate a minimal number of false alarms 3. to be highly sensitive to ischemic episodes and above all to the most dangerous ones. We start this paper by mentioning some related work, followed by a description of the transient ischemia detection algorithm. We finish presenting the performances of the algorithm and conclusions. Related work and materialsThe ischemic transient events are associated with variations (elevations or depressions) of the ST segment in the ECG signal. Nevertheless, similar variations may be also produced by diurnal changes, postural changes, changes in ventricular conduction which make difficult the distinction between ischemic and non-ischemic events. There are several distinct algorithms that address the automatically ischemic detection in the ECG signals applying different methods that consider time domain analysis, KL transform, neural network or fuzzy logic. Nevertheless only a few of them deal explicitly with non-ischemic events such as axis shift events (an interesting reference of the existing ischemia algorithms can be found in [1]). Moreover the majority of the existing algorithms are difficult to be adjusted for real time execution and up to our knowledge, only a few algorithms specia...