A versatile trigger and synchronization module with IEEE1588 capabilities and EPICS support.

Event timing and synchronization are two key aspects to improve in the implementation of distributed data acquisition (dDAQ) systems such as the ones used in fusion experiments. It is also of great importance the integration of dDAQ in control and measurement networks. This paper analyzes the applicability of the IEEE1588 and EPICS standards to solve these problems, and presents a hardware module implementation based in both of them that allow adding these functionalities to any DAQ. The IEEE1588 standard facilitates the integration of event timing and synchronization mechanisms in distributed data acquisition systems based on IEEE 803.3 (Ethernet). An optimal implementation of such system requires the use of network interface devices which include specific hardware resources devoted to the IEE1588 functionalities. Unfortunately, this is not the approach followed in most of the large number of applications available nowadays. Therefore, most solutions are based in software and use standard hardware network interfaces. This paper presents the development of a hardware module (GI2E) with IEEE1588 capabilities which includes USB, RS232, RS485 and CAN interfaces. This permits to integrate any DAQ element that uses these interfaces in dDAQ systems in an efficient and simple way. The module has been developed with Motorola's Coldfire MCF5234 processor and National Semiconductors's PHY DP83640T, providing it with the possibility to implement the PTP protocol of IEEE1588 by hardware, and therefore increasing its performance over other implementations based in software. To facilitate the integration of the dDAQ system in control and measurement networks the module includes a basic Input/Output Controller (IOC) functionality of the Experimental Physics and Industrial Control System (EPICS) architecture. The paper discusses the implementation details of this module and presents its applications in advanced dDAQ applications in the fusion community

Data reduction in the ITMS system through a data acquisition model with self-adaptive sampling rate

Long pulse or steady state operation of fusion experiments require data acquisition and processing systems that reduce the volume of data involved. The availability of self-adaptive sampling rate systems and the use of real-time lossless data compression techniques can help solve these problems. The former is important for continuous adaptation of sampling frequency for experimental requirements. The latter allows the maintenance of continuous digitization under limited memory conditions. This can be achieved by permanent transmission of compressed data to other systems. The compacted transfer ensures the use of minimum bandwidth. This paper presents an implementation based on intelligent test and measurement system (ITMS), a data acquisition system architecture with multiprocessing capabilities that permits it to adapt the system’s sampling frequency throughout the experiment. The sampling rate can be controlled depending on the experiment’s specific requirements by using an external dc voltage signal or by defining user events through software. The system takes advantage of the high processing capabilities of the ITMS platform to implement a data reduction mechanism based in lossless data compression algorithms which are themselves based in periodic deltas

Event Recognition Using Signal Spectrograms in Long Pulse Experiments

As discharge duration increases, real-time complex analysis of the signal becomes more important. In this context, data acquisition and processing systems must provide models for designing experiments which use event oriented plasma control. One example of advanced data analysis is signal classification. The off-line statistical analysis of a large number of discharges provides information to develop algorithms for the determination of the plasma parameters from measurements of magnetohydrodinamic waves, for example, to detect density fluctuations induced by the Alfvén cascades using morphological patterns. The need to apply different algorithms to the signals and to address different processing algorithms using the previous results necessitates the use of an event-based experiment. The Intelligent Test and Measurement System platform is an example of architecture designed to implement distributed data acquisition and real-time processing systems. The processing algorithm sequence is modeled using an event-based paradigm. The adaptive capacity of this model is based on the logic defined by the use of state machines in SCXML. The Intelligent Test and Measurement System platform mixes a local multiprocessing model with a distributed deployment of services based on Jini

La práctica del ciclismo indoor en los mayores: implicaciones metodológicas

Uno de los cambios más característicos de la época tecnológica en la que nos encontramos inmersos, es el envejecimiento de la población y la consecuente inversión de la pirámide poblacional. Dicha inversión, acentúa la necesidad de diseñar y extender planes de actuación que promuevan actividades físico-recreativas continuadas con intensidades, cargas y ejercicios específicos totalmente adaptados a las características de esta población. La propuesta que aquí presentamos se basa en la práctica del ciclo indoor, que representa una experiencia fundamental para el desarrollo integral de la persona. Esta práctica puede considerarse una terapia imprescindible para la estimulación y reeducación de las habilidades concretas de esta población, así como para la adquisición de técnicas de comunicación social, a la vez que realizan una actividad lúdica y placentera. Mediante un programa de actividad física de este tipo, se pretende aumentar las posibilidades funcionales, al tiempo que se mejora las psico-afectivas, y con ello la calidad de vida de nuestros mayores

Low-lying magnetic loops in the solar internetwork

The aim of this work is to study the structure of the magnetic field vector in the internetwork and search for the presence of small-scale loops. We invert 1.56 micron spectropolarimetric observations of internetwork regions at disc centre by applying the SIR code. This allows us to recover the atmospheric parameters that play a role in the formation of these spectral lines. We are mainly interested in the structure of the magnetic field vector. We find that many opposite polarity elements of the internetwork are connected by short (2-6''), low-lying (photospheric) loops. These loops connect at least the 10-20 % of the internetwork flux visible in our data. Also we have some evidence that points towards a dynamic scenario which can be produced by the emergence of internetwork magnetic flux.Comment: Accepted for publication in A&A letter

Partículas superparamagnéticas ultrapequeñas de óxido de hierro para aplicaciones biomédicas

Las partículas superparamagnéticas ultrapequeñas de óxido de hierro (USPIO) tienen una enorme utilidad enBiomedicina como agentes de contraste en resonancia magnética de imagen o como sistemas transportadores defármacos, entre otras aplicaciones. La naturaleza del recubrimiento de los núcleos inorgánicos de las partículasUSPIO determina su estabilidad in vitro y su comportamiento in vivo, siendo especialmente importantes sus propiedadesfi sicoquímicas, en concreto el tamaño, la carga superfi cial y la densidad del recubrimiento. Las pequeñasdimensiones de las partículas USPIO hace difícil una caracterización fi sicoquímica completa, la cuál es de sumaimportancia para poder mejorar su estabilidad y comportamiento in vivo. Esta revisión se centra en las técnicasinstrumentales utilizadas en el análisis de los núcleos magnéticos y de sus recubrimientos orgánicos

Statistical Complexity and Nontrivial Collective Behavior in Electroencephalografic Signals

We calculate a measure of statistical complexity from the global dynamics of electroencephalographic (EEG) signals from healthy subjects and epileptic patients, and are able to stablish a criterion to characterize the collective behavior in both groups of individuals. It is found that the collective dynamics of EEG signals possess relative higher values of complexity for healthy subjects in comparison to that for epileptic patients. To interpret these results, we propose a model of a network of coupled chaotic maps where we calculate the complexity as a function of a parameter and relate this measure with the emergence of nontrivial collective behavior in the system. Our results show that the presence of nontrivial collective behavior is associated to high values of complexity; thus suggesting that similar dynamical collective process may take place in the human brain. Our findings also suggest that epilepsy is a degenerative illness related to the loss of complexity in the brain.Comment: 13 pages, 3 figure