Comunicación digital. Nuevos yacimientos de empleo y formación

El progreso de las Tecnologías de la Información y la Comunicación (TIC), y en concreto su aplicación al desarrollo de Internet, están transformando rápidamente el sistema de producción y, consecuentemente, los perfiles profesionales demandados. Recordemos que entendemos por perfil profesional el conjunto de conocimientos, habilidades, competencias y aptitudes que hacen a un profesional competitivo en un determinado mercado de trabajo. En este artículo reflexionaremos sobre el mercado de trabajo de los ‘comunicadores digitales' que surgen de la evolución de Internet y que encuentran su campo de actuación en las nuevas formas de comunicación interpersonal, los nuevos medios de comunicación social y entretenimiento y en la comunicación de empresas e instituciones con sus clientes y proveedores. Uno de los principales yacimientos de nuevos empleos en la economía del conocimiento europea, según vaticinan todos los informes

Magnetoencephalography as a putative biomarker for Alzheimer's disease.

Alzheimer’s Disease (AD) is the most common dementia in the elderly and is estimated to affect tens of millions of people worldwide. AD is believed to have a prodromal stage lasting ten or more years. While amyloid deposits, tau filaments, and loss of brain cells are characteristics of the disease, the loss of dendritic spines and of synapses predate such changes. Popular preclinical detection strategies mainly involve cerebrospinal fluid biomarkers, magnetic resonance imaging, metabolic PET scans, and amyloid imaging. One strategy missing from this list involves neurophysiological measures, which might be more sensitive to detect alterations in brain function. The Magnetoencephalography International Consortium of Alzheimer’s Disease arose out of the need to advance the use of Magnetoencephalography (MEG), as a tool in AD and pre-AD research. This paper presents a framework for using MEG in dementia research, and for short-term research priorities

Suppression of the intrinsic stochastic pinning of domain walls in magnetic nanostripes

Nanofabrication has allowed the development of new concepts such as magnetic logic and race-track memory, both of which are based on the displacement of magnetic domain walls on magnetic nanostripes. One of the issues that has to be solved before devices can meet the market demands is the stochastic behaviour of the domain wall movement in magnetic nanostripes. Here we show that the stochastic nature of the domain wall motion in permalloy nanostripes can be suppressed at very low fields (0.6-2.7 Oe). We also find different field regimes for this stochastic motion that match well with the domain wall propagation modes. The highest pinning probability is found around the precessional mode and, interestingly, it does not depend on the external field in this regime. These results constitute an experimental evidence of the intrinsic nature of the stochastic pinning of domain walls in soft magnetic nanostripes

Low-Profile Dual Circularly Polarized Antenna Array for Satellite Communications in the X Band

A planar antenna is introduced that works as a portable system for X-band satellite communications. This antenna is low-profile and modular with dimensions of 40 × 40 × 2.5 × cm. It is composed of a square array of 144 printed circuit elements that cover a wide bandwidth (14.7%) for transmission and reception along with dual and interchangeable circular polarization. A radiation efficiency above 50% is achieved by a low-loss stripline feeding network. This printed antenna has a 3 dB beamwidth of 5°, a maximum gain of 26 dBi and an axial ratio under 1.9 dB over the entire frequency band. The complete design of the antenna is shown, and the measurements are compared with simulations to reveal very good agreement.

From irradiance to output power fluctuations: the pv plant as a low pass filter

The power generated by large grid-connected photovoltaic (PV) plants depends greatly on the solar irradiance. This paper studies the effects of the solar irradiance variability analyzing experimental 1-s data collected throughout a year at six PV plants, totaling 18 MWp. Each PV plant was modeled as a first order filter function based on an analysis in the frequency domain of the irradiance data and the output power signals. An empiric expression which relates the filter parameters and the PV plant size has been proposed. This simple model has been successfully validated precisely determining the daily maximum output power fluctuation from incident irradiance measurements.

Tracking and back-tracking

This paper presents a review of back-tracking geometry not only for single axis but also for two-axis tracking and analyses the corresponding energy gains. It compares the different back-tracking strategies with the ideal tracking in terms of energy yield concluding, on the one hand, that back-tracking is more useful for single horizontal axis than for the single vertical one, and on the other hand, that back-tracking is more efficient when applied in the primary axis of a two-axis tracker

Biomaterials from beer manufacture waste for bone growth scaffolds

Agricultural wastes are a source of renewable raw materials (RRM), with structures that can be tailored for the use envisaged. Here, they have proved to be good replacement candidates for use as biomaterials for the growth of osteoblasts in bone replacement therapies. Their preparation is more cost effective than that of materials presently in use with the added bonus of converting a low-cost waste into a value-added product. Due to their origin these solids are ecomaterials. In this study, several techniques, including X-ray diffraction (XRD), chemical analysis, mercury intrusion porosimetry (MIP), scanning electron microscopy (SEM), and bioassays, were used to compare the biocompatibility and cell growth of scaffolds produced from beer bagasse, a waste material from beer production, with a control sample used in bone and dental regenerative processes.

Influence of Current Pulse Shape on Directly Modulated Systems Performance in Metro Area Optical Networks

Due to the fact that a metro network market is very cost sensitive, direct modulated schemes appear attractive. In this paper a CWDM (Coarse Wavelength Division Multiplexing) system is studied in detail by means of an Optical Communication System Design Software; a detailed study of the modulated current shape (exponential, sine and gaussian) for 2.5 Gb/s CWDM Metropolitan Area Networks is performed to evaluate its tolerance to linear impairments such as signal-to-noise-ratio degradation and dispersion. Point-to-point links are investigated and optimum design parameters are obtained. Through extensive sets of simulation results, it is shown that some of these shape pulses are more tolerant to dispersion when compared with conventional gaussian shape pulses. In order to achieve a low Bit Error Rate (BER), different types of optical transmitters are considered including strongly adiabatic and transient chirp dominated Directly Modulated Lasers (DMLs). We have used fibers with different dispersion characteristics, showing that the system performance depends, strongly, on the chosen DML?fiber couple.

Self-validating technique for the measurement of the linewidth enhancement factor in semiconductor lasers

A new method for measuring the linewidth enhancement factor (α-parameter) of semiconductor lasers is proposed and discussed. The method itself provides an estimation of the measurement error, thus self-validating the entire procedure. The α-parameter is obtained from the temporal profile and the instantaneous frequency (chirp) of the pulses generated by gain switching. The time resolved chirp is measured with a polarization based optical differentiator. The accuracy of the obtained values of the α-parameter is estimated from the comparison between the directly measured pulse spectrum and the spectrum reconstructed from the chirp and the temporal profile of the pulse. The method is applied to a VCSEL and to a DFB laser emitting around 1550 nm at different temperatures, obtaining a measurement error lower than ± 8%.

An Experimental Platform for large-scale research facing FI-IoT scenarios

Providing experimental facilities for the Internet of Things (IoT) world is of paramount importance to materialise the Future Internet (FI) vision. The level of maturity achieved at the networking level in Sensor and Actuator networks (SAN) justifies the increasing demand on the research community to shift IoT testbed facilities from the network to the service and information management areas. In this paper we present an Experimental Platform fulfilling these needs by: integrating heterogeneous SAN infrastructures in a homogeneous way; providing mechanisms to handle information, and facilitating the development of experimental services. It has already been used to deploy applications in three different field trials: smart metering, smart places and environmental monitoring and it will be one of the components over which the SmartSantander project, that targets a large-scale IoT experimental facility, will rely on

Detección y seguimiento de objetos en vídeos de actividades de vida diaria para rehabilitación de pacientes con daño cerebral adquirido

Las técnicas de rehabilitación permiten la recuperación y mejora de las funciones dañadas o deterioradas y ayuda al paciente con DCA a adaptarse a su nueva situación. El avance tecnológico que se ha producido en las últimas décadas, ha impulsado la investigación en el diseño y desarrollo de nuevos modelos de rehabilitación. La tecnología de vídeo interactivo se convierte en un elemento de apoyo en estos nuevos modelos rehabilitadores. Se hace necesario desarrollar nuevos algoritmos de segmentación y seguimiento que permitan dotar de información adicional a los vídeos. En este trabajo se han implementado y evaluado dos métodos que permiten realizar la detección y el seguimiento de objetos de interés.

Optimized edge appearance probability for cooperative localization based on tree-reweighted nonparametric belief propagation

Nonparametric belief propagation (NBP) is a well-known particle-based method for distributed inference in wireless networks. NBP has a large number of applications, including cooperative localization. However, in loopy networks NBP suffers from similar problems as standard BP, such as over-confident beliefs and possible nonconvergence. Tree-reweighted NBP (TRW-NBP) can mitigate these problems, but does not easily lead to a distributed implementation due to the non-local nature of the required so-called edge appearance probabilities. In this paper, we propose a variation of TRWNBP, suitable for cooperative localization in wireless networks. Our algorithm uses a fixed edge appearance probability for every edge, and can outperform standard NBP in dense wireless networks.

Particle filtering for indoor RFID tag tracking

In this paper, we propose a particle filtering (PF) method for indoor tracking using radio frequency identification (RFID) based on aggregated binary measurements. We use an Ultra High Frequency (UHF) RFID system that is composed of a standard RFID reader, a large set of standard passive tags whose locations are known, and a newly designed, special semi-passive tag attached to an object that is tracked. This semi-passive tag has the dual ability to sense the backscatter communication between the reader and other passive tags which are in its proximity and to communicate this sensed information to the reader using backscatter modulation. We refer to this tag as a sense-a-tag (ST). Thus, the ST can provide the reader with information that can be used to determine the kinematic parameters of the object on which the ST is attached. We demonstrate the performance of the method with data obtained in a laboratory environment.

Uniformly reweighted belief propagation for distributed Bayesian hypothesis testing

Belief propagation (BP) is a technique for distributed inference in wireless networks and is often used even when the underlying graphical model contains cycles. In this paper, we propose a uniformly reweighted BP scheme that reduces the impact of cycles by weighting messages by a constant ?edge appearance probability? rho ? 1. We apply this algorithm to distributed binary hypothesis testing problems (e.g., distributed detection) in wireless networks with Markov random field models. We demonstrate that in the considered setting the proposed method outperforms standard BP, while maintaining similar complexity. We then show that the optimal ? can be approximated as a simple function of the average node degree, and can hence be computed in a distributed fashion through a consensus algorithm.

Uniformly Reweighted Belief Propagation: A Factor Graph Approach

Tree-reweighted belief propagation is a message passing method that has certain advantages compared to traditional belief propagation (BP). However, it fails to outperform BP in a consistent manner, does not lend itself well to distributed implementation, and has not been applied to distributions with higher-order interactions. We propose a method called uniformly-reweighted belief propagation that mitigates these drawbacks. After having shown in previous works that this method can substantially outperform BP in distributed inference with pairwise interaction models, in this paper we extend it to higher-order interactions and apply it to LDPC decoding, leading performance gains over BP.