Adaptive Randomized Distributed Space-Time Coding in Cooperative MIMO Relay Systems

An adaptive randomized distributed space-time coding (DSTC) scheme and algorithms are proposed for two-hop cooperative MIMO networks. Linear minimum mean square error (MMSE) receivers and an amplify-and-forward (AF) cooperation strategy are considered. In the proposed DSTC scheme, a randomized matrix obtained by a feedback channel is employed to transform the space-time coded matrix at the relay node. Linear MMSE expressions are devised to compute the parameters of the adaptive randomized matrix and the linear receive filter. A stochastic gradient algorithm is also developed to compute the parameters of the adaptive randomized matrix with reduced computational complexity. We also derive the upper bound of the error probability of a cooperative MIMO system employing the randomized space-time coding scheme first. The simulation results show that the proposed algorithms obtain significant performance gains as compared to existing DSTC schemes.Comment: 4 figure

Distributed Space-Time Coding Based on Adjustable Code Matrices for Cooperative MIMO Relaying Systems

An adaptive distributed space-time coding (DSTC) scheme is proposed for two-hop cooperative MIMO networks. Linear minimum mean square error (MMSE) receive filters and adjustable code matrices are considered subject to a power constraint with an amplify-and-forward (AF) cooperation strategy. In the proposed adaptive DSTC scheme, an adjustable code matrix obtained by a feedback channel is employed to transform the space-time coded matrix at the relay node. The effects of the limited feedback and the feedback errors are assessed. Linear MMSE expressions are devised to compute the parameters of the adjustable code matrix and the linear receive filters. Stochastic gradient (SG) and least-squares (LS) algorithms are also developed with reduced computational complexity. An upper bound on the pairwise error probability analysis is derived and indicates the advantage of employing the adjustable code matrices at the relay nodes. An alternative optimization algorithm for the adaptive DSTC scheme is also derived in order to eliminate the need for the feedback. The algorithm provides a fully distributed scheme for the adaptive DSTC at the relay node based on the minimization of the error probability. Simulation results show that the proposed algorithms obtain significant performance gains as compared to existing DSTC schemes.Comment: 6 figure

Fracture of a model cohesive granular material

We study experimentally the fracture mechanisms of a model cohesive granular medium consisting of glass beads held together by solidified polymer bridges. The elastic response of this material can be controlled by changing the cross-linking of the polymer phase, for example. Here we show that its fracture toughness can be tuned over an order of magnitude by adjusting the stiffness and size of the polymer bridges. We extract a well-defined fracture energy from fracture testing under a range of material preparations. This energy is found to scale linearly with the cross-sectional area of the bridges. Finally, X-ray microcomputed tomography shows that crack propagation is driven by adhesive failure of about one polymer bridge per bead located at the interface, along with microcracks in the vicinity of the failure plane. Our findings provide insight into the fracture mechanisms of this model material, and the mechanical properties of disordered cohesive granular media in general

Acceso abierto a las publicaciones científicas : definición, recursos, copyright e impacto

Publicado en: El Profesional de la Información 15(4): pp. 255-66 (2005)El movimiento a favor del acceso abierto a las publicaciones científicas (Open access) cada vez tiene más adeptos y apoyo, tanto institucional como de los miembros de la comunidad científica, y también son numerosas las manifestaciones e iniciativas en torno al mismo. Este artículo analiza el significado de Open access o Acceso abierto a las publicaciones científicas a través de internet de acuerdo con las declaraciones de Budapest, Bethesda y Berlín. Se revisan algunos aspectos relacionados con el impacto de las revistas OA y las implicaciones de la cesión de derechos de copyright en el acceso abierto. Por último se evalúan las perspectivas de futuro del acceso en abierto desde el punto de vista de las políticas.Peer reviewe

Development and validation of a reinforcement learning algorithm to dynamically optimize mechanical ventilation in critical care.

The aim of this work was to develop and evaluate the reinforcement learning algorithm VentAI, which is able to suggest a dynamically optimized mechanical ventilation regime for critically-ill patients. We built, validated and tested its performance on 11,943 events of volume-controlled mechanical ventilation derived from 61,532 distinct ICU admissions and tested it on an independent, secondary dataset (200,859 ICU stays; 25,086 mechanical ventilation events). A patient "data fingerprint" of 44 features was extracted as multidimensional time series in 4-hour time steps. We used a Markov decision process, including a reward system and a Q-learning approach, to find the optimized settings for positive end-expiratory pressure (PEEP), fraction of inspired oxygen (FiO2) and ideal body weight-adjusted tidal volume (Vt). The observed outcome was in-hospital or 90-day mortality. VentAI reached a significantly increased estimated performance return of 83.3 (primary dataset) and 84.1 (secondary dataset) compared to physicians' standard clinical care (51.1). The number of recommended action changes per mechanically ventilated patient constantly exceeded those of the clinicians. VentAI chose 202.9% more frequently ventilation regimes with lower Vt (5-7.5 mL/kg), but 50.8% less for regimes with higher Vt (7.5-10 mL/kg). VentAI recommended 29.3% more frequently PEEP levels of 5-7 cm H2O and 53.6% more frequently PEEP levels of 7-9 cmH2O. VentAI avoided high (>55%) FiO2 values (59.8% decrease), while preferring the range of 50-55% (140.3% increase). In conclusion, VentAI provides reproducible high performance by dynamically choosing an optimized, individualized ventilation strategy and thus might be of benefit for critically ill patients