University of Patras

About: University of Patras is a education organization based out in Pátrai, Greece. It is known for research contribution in the topics: Population & Catalysis. The organization has 13372 authors who have published 31263 publications receiving 677159 citations. The organization is also known as: Panepistímio Patrón.

Identification of coupling direction: application to cardiorespiratory interaction.

Abstract: We consider the problem of experimental detection of directionality of weak coupling between two self-sustained oscillators from bivariate data. We further develop the method introduced by Rosenblum and Pikovsky [Phys. Rev. E 64, 045202 (2001)], suggesting an alternative approach. Next, we consider another framework for identification of directionality, based on the idea of mutual predictability. Our algorithms provide directionality index that shows whether the coupling between the oscillators is unidirectional or bidirectional, and quantifies the asymmetry of bidirectional coupling. We demonstrate the efficiency of three different algorithms in determination of directionality index from short and noisy data. These techniques are then applied to analysis of cardiorespiratory interaction in healthy infants. The results reveal that the direction of coupling between cardiovascular and respiratory systems varies with the age within the first 6 months of life. We find a tendency to change from nearly symmetric bidirectional interaction to nearly unidirectional one (from respiration to the cardiovascular system).

Selective methanation of CO over supported noble metal catalysts: Effects of the nature of the metallic phase on catalytic performance

Abstract: The catalytic performance of Al2O3-supported noble metal catalysts for the methanation of CO, CO2 and their mixture has been investigated with respect to the nature of the dispersed metallic phase (Ru, Rh, Pt, Pd). Experiments have been conducted using feed compositions relevant to those of reformate gas streams, both in the absence and in the presence of water. It has been found that, for all experimental conditions investigated, Ru and Rh are significantly more active than Pt and Pd. Selectivity toward hydrogenation products depends strongly on the noble metal catalyst employed, as well as on whether solo- or co-methanation of CO/CO2 is occuring. For hydrogenation of CO alone, selectivity toward CH4 increases with increasing temperature at the expense of higher hydrocarbons. In presence of water in the feed, catalytic activity of Ru is not affected, while that of Rh is reduced. On the other hand, the performance of Pt and Pd is poor since they promote the undesired water-gas shift (WGS) reaction. In hydrogenation of CO2 alone, selectivity toward higher hydrocarbons is negligible for all catalysts investigated but the reaction is accompanied by production of CO via the reverse WGS reaction. In all cases, addition of water in the feed results in decrease of catalytic activity. In combined hydrogenation of CO/CO2 mixtures, conversion of CO2 is completely suppressed until conversion of CO reaches its maximum value. Selectivity toward methane, which is typically higher than 70%, increases with increasing temperature and approaches 100% when CO2 conversion is initiated. Addition of 30% water vapor in the feed does not affect CO hydrogenation over Ru and Rh catalysts but retards CO2 hydrogenation, thereby expanding the temperature window of operation.

Parallel differential evolution

Abstract: Parallel processing has emerged as a key enabling technology in modern computing. Recent software advances have allowed collections of heterogeneous computers to be used as a concurrent computational resource. In this work we explore how differential evolution can be parallelized, using a ring-network topology, so as to improve both the speed and the performance of the method. Experimental results indicate that the extent of information exchange among subpopulations assigned to different processor nodes, bears a significant impact on the performance of the algorithm. Furthermore, not all the mutation strategies of the differential evolution algorithm are equally sensitive to the value of this parameter.