University of Alcalá

About: University of Alcalá is a education organization based out in Alcalá de Henares, Spain. It is known for research contribution in the topics: Population & Receptor. The organization has 10795 authors who have published 20718 publications receiving 410089 citations. The organization is also known as: University of Alcala & University of Alcala de Henares.

Herschel-PACS Observations of Far-IR CO Line Emission in NGC 1068: Highly Excited Molecular Gas in the Circumnuclear Disk

Abstract: We report the detection of far-IR CO rotational emission from the prototypical Seyfert 2 galaxy NGC 1068. Using Herschel-PACS, we have detected 11 transitions in the J_(upper) = 14-30 (E_(upper)/k_B = 580-2565 K) range, all of which are consistent with arising from within the central 10" (700 pc). The detected transitions are modeled as arising from two different components: a moderate-excitation (ME) component close to the galaxy systemic velocity and a high-excitation (HE) component that is blueshifted by ~80 km s^(–1). We employ a large velocity gradient model and derive n_(H2) ~ 10^(5.6) cm^(–3), T_(kin) ~ 170 K, and M_(H2) ~ 10^(6.7) M_☉ for the ME component and n_(H2) ~ 10^(6.4) cm^(–3), T_(kin) ~ 570 K, and M_(H2) ~ 10^(5.6) M_☉ for the HE component, although for both components the uncertainties in the density and mass are ±(0.6-0.9) dex. Both components arise from denser and possibly warmer gas than traced by low-J CO transitions, and the ME component likely makes a significant contribution to the mass budget in the nuclear region. We compare the CO line profiles with those of other molecular tracers observed at higher spatial and spectral resolution and find that the ME transitions are consistent with these lines arising in the ~200 pc diameter ring of material traced by H_2 1-0 S(1) observations. The blueshift of the HE lines may also be consistent with the bluest regions of this H_2 ring, but a better kinematic match is found with a clump of infalling gas ~40 pc north of the active galactic nucleus (AGN). We consider potential heating mechanisms and conclude that X-ray- or shock heating of both components is viable, while far-UV heating is unlikely. We discuss the prospects of placing the HE component near the AGN and conclude that while the moderate thermal pressure precludes an association with the ~1 pc radius H_2O maser disk, the HE component could potentially be located only a few parsecs more distant from the AGN and might then provide the N_H ~ 10^(25) cm^(–2) column obscuring the nuclear hard X-rays. Finally, we also report sensitive upper limits extending up to J_(upper) = 50, which place constraints on a previous model prediction for the CO emission from the X-ray obscuring torus.

Feature selection in machine learning prediction systems for renewable energy applications

Abstract: This paper focuses on feature selection problems that arise in renewable energy applications. Feature selection is an important problem in machine learning, both in classification and regression problems. In renewable energy systems, feature selection appears related to prediction systems in the most important sources such as wind, solar and marine resources. The objective of the paper is twofold: first, a review of the most important prediction systems for renewable energy applications involving feature selection is carried out. Analysis and discussion of different feature selection problems in prediction systems are considered. We show that wrapper FSP approaches are those mostly used due to their higher performance. They include a diversity of algorithms, prevailing fast-training approaches. The lack of an uniform framework for FSP and the diversity of tackled problems impede a systematic assessment of the performance and properties of the applied methods. Thus, the simultaneously use of several global search mechanisms should be the preferred option. In a second part of the paper, we explore this possibility, by introducing a novel approach for feature selection based on a novel meta-heuristic, the Coral Reefs Optimization algorithm with Substrate Layer. This approach is able to combine different search mechanisms into a single algorithm, providing a global search procedure of high quality. We use an Extreme Learning Machine for prediction within this novel approach. The performance of the system is evaluated in a problem of wind speed prediction from numerical models input, using real data from a wind farm in Spain, where comparison with alternative regression algorithms is carried out. Improvements up to 20% in hourly and daily wind speed prediction are obtained with the proposed system versus the algorithms without the feature selection process considered.

Functional traits and plasticity in response to light in seedlings of four Iberian forest tree species.

Abstract: We investigated the differential roles of physiological and morphological features on seedling survivorship along an experimental irradiance gradient in four dominant species of cool temperate-Mediterranean forests (Quercus robur L., Quercus pyrenaica Willd., Pinus sylvestris L. and Pinus pinaster Ait.). The lowest photochemical efficiency (Fv/Fm in dark-adapted leaves) was reached in deep shade (1% of full sunlight) in all species except Q. robur, which had the lowest photochemical efficiency in both deep shade and 100% of full sunlight. Species differed significantly in their survival in 1% of full sunlight but exhibited similar survivorship in 6, 20 and 100% of full sunlight. Shade-tolerant oaks had lower leaf area ratios, shoot to root ratios, foliage allocation ratios and higher rates of allocation to structural biomass (stem plus thick roots) than shade-intolerant pines. Overall phenotypic plasticity for each species, estimated as the difference between the minimum and the maximum mean values of the ecophysiological variables studied at the various irradiances divided by the maximum mean value of those variables, was inversely correlated with shade tolerance. Observed morphology, allocation and plasticity conformed to a conservative resource-use strategy, although observed differences in specific leaf area, which was higher in shade-tolerant species, supported a carbon gain maximization strategy. Lack of a congruent suite of traits underlying shade tolerance in the studied species provides evidence of adaptation to multiple selective forces. Although the study was based on only four species, the importance of ecophysiological variables as determinants of interspecific differences in survival in limiting light was demonstrated.