Linealización de un Enlace RoF mediante la Transformada Wavelet Estacionaria

Se presenta una nueva técnica de modelado del DPD para mejorar la linealización de enlaces de radio sobre fibra (RoF). Dicha técnica consiste en la descomposición de la señal original en niveles multirresolución mediante la SWT. Se utilizarán señales del estándar LTE y se evaluarán los resultados comparando el método propuesto con el modelo polinomial clásico en base al ACPR, NMSE y el EVM

Linealización de Amplificadores de Potencia RF mediante Transformada Wavelet

Se presenta una nueva técnica para el modelado de amplificadores de potencia de banda ancha (AP) y diseño de predistorsionadores digitales (DPD). Dicha técnica consiste en descomponer la señal original en niveles multirresolución mediante la Transformada Wavelet. Se evaluará en un sistema de Radio Cognitiva WRAN (IEEE 802.22)

Maize open-pollinated populations physiological improvement: validating tools for drought response participatory selection

Participatory selection—exploiting specific adaptation traits to target environments—helps to guarantees yield stability in a changing climate, in particular under low-input or organic production. The purpose of the present study was to identify reliable, low-cost, fast and easy-to-use tools to complement traditional selection for an e ective participatory improvement of maize populations for drought resistance/tolerance. The morphological and eco-physiological responses to progressive water deprivation of four maize open-pollinated populations were assessed in both controlled and field conditions. Thermography and Chl a fluorescence, validated by gas exchange indicated that the best performing populations under water-deficit conditions were ‘Fandango’ and to a less extent ‘Pigarro’ (both from participatory breeding). These populations showed high yield potential under optimal and reduced watering. Under moderate water stress, ‘Bilhó’, originating from an altitude of 800 m, is one of the most resilient populations. The experiments under chamber conditions confirmed the existence of genetic variability within ‘Pigarro’ and ‘Fandango’ for drought response relevant for future populations breeding. Based on the easiness to score and population discriminatory power, the performance index (PIABS) emerges as an integrative phenotyping tool to use as a refinement of the common participatory maize selection especially under moderate water deprivationinfo:eu-repo/semantics/publishedVersio

Linealización mediante Predistorsión Digital de un Sistema Radio sobre Fibra de Doble Banda

En este artículo se propone la linealización de un sistema Radio-over-Fiber (RoF) de doble banda  mediante predistorsión digital. Los resultados han sido evaluados experimentalmente con señales LTE en un sistema RoF, obteniendo mejores resultados que con el predistorsionador clásico de una banda en términos de Adjacent Channel Power Ratio (ACPR), pérdidas de potencia y Error Vector Magnitude (EVM).

Estimating and Modelling Bias of the Hierarchical Partitioning Public-Domain Software: Implications in Environmental Management and Conservation

BACKGROUND: Hierarchical partitioning (HP) is an analytical method of multiple regression that identifies the most likely causal factors while alleviating multicollinearity problems. Its use is increasing in ecology and conservation by its usefulness for complementing multiple regression analysis. A public-domain software "hier.part package" has been developed for running HP in R software. Its authors highlight a "minor rounding error" for hierarchies constructed from >9 variables, however potential bias by using this module has not yet been examined. Knowing this bias is pivotal because, for example, the ranking obtained in HP is being used as a criterion for establishing priorities of conservation. METHODOLOGY/PRINCIPAL FINDINGS: Using numerical simulations and two real examples, we assessed the robustness of this HP module in relation to the order the variables have in the analysis. Results indicated a considerable effect of the variable order on the amount of independent variance explained by predictors for models with >9 explanatory variables. For these models the nominal ranking of importance of the predictors changed with variable order, i.e. predictors declared important by its contribution in explaining the response variable frequently changed to be either most or less important with other variable orders. The probability of changing position of a variable was best explained by the difference in independent explanatory power between that variable and the previous one in the nominal ranking of importance. The lesser is this difference, the more likely is the change of position. CONCLUSIONS/SIGNIFICANCE: HP should be applied with caution when more than 9 explanatory variables are used to know ranking of covariate importance. The explained variance is not a useful parameter to use in models with more than 9 independent variables. The inconsistency in the results obtained by HP should be considered in future studies as well as in those already published. Some recommendations to improve the analysis with this HP module are given