On the nature of the near-UV extended light in Seyfert galaxies

We study the nature of the extended near-UV emission in the inner kiloparsec of a sample of 15 Seyfert (Sy) galaxies which have both near-UV (F330W) and narrow-band [O  iii ] high-resolution Hubble images. For the majority of the objects, we find a very similar morphology in both bands. From the [O  iii ] images, we construct synthetic images of the nebular continuum plus the emission-line contribution expected through the F330W filter, which can be subtracted from the F330W images. We find that the emission of the ionized gas dominates the near-UV extended emission in half of the objects. A further broad-band photometric study, in the bands F330W ( U ), F547M ( V ) and F160W ( H ), shows that the remaining emission is dominated by the underlying galactic bulge contribution. We also find a blue component whose nature is not clear in four out of 15 objects. This component may be attributed to scattered light from the active galactic nuclei, to a young stellar population in unresolved star clusters, or to early disrupted clusters. Star-forming regions and/or bright off nuclear star clusters are observed in 4/15 galaxies of the sample.     

Pleistocene–Holocene environmental change in the Canary Archipelago as inferred from the stable isotope composition of land snail shells

The isotopic composition of land snail shells was analyzed to investigate environmental changes in the eastern Canary Islands (28–29°N) over the last ~ 50 ka. Shell δ¹³C values range from −8.9‰ to 3.8‰. At various times during the glacial interval (~ 15 to ~ 50 ka), moving average shell δ¹³C values were 3‰ higher than today, suggesting a larger proportion of C₄ plants at those periods. Shell δ¹⁸O values range from −1.9‰ to 4.5‰, with moving average δ¹⁸O values exhibiting a noisy but long-term increase from 0.1‰ at ~ 50 ka to 1.6–1.8‰ during the LGM (~ 15–22 ka). Subsequently, the moving average δ¹⁸O values range from 0.0‰ at ~ 12 ka to 0.9‰ at present. Calculations using a published snail flux balance model for δ¹⁸O, constrained by regional temperatures and ocean δ¹⁸O values, suggest that relative humidity at the times of snail activity fluctuated but exhibited a long-term decline over the last ~ 50 ka, eventually resulting in the current semiarid conditions of the eastern Canary Islands (consistent with the aridification process in the nearby Sahara). Thus, low-latitude oceanic island land snail shells may be isotopic archives of glacial to interglacial and tropical/subtropical environmental change.     

A high-resolution stellar library for evolutionary population synthesis

We present a library of 1654 high-resolution stellar spectra, with a sampling of 0.3 Å and covering the wavelength range from 3000 to 7000 Å. The library was computed with the latest improvements in stellar atmospheres, incorporating non-local thermodynamic equilibrium (non-LTE) line-blanketed models for hot, massive  ( T _eff≥ 27 500 K)  and line-blanketed models for cool  (3000 ≤ T _eff≤ 4500 K)  stars. The total coverage of the grid is  3000 K ≤ T _eff≤ 55 000 K  and  −0.5 ≤ log g ≤ 5.5  , for four chemical abundance values: twice solar, solar, half solar and 1/10 solar. Evolutionary synthesis models using this library are presented in a companion paper. We tested the general behaviour of the library by calculating and comparing equivalent widths of numerous H and He  i lines, and some of the commonly used metallic indices. We also compared the library with the empirical libraries STELIB and Indo-US. The full set of the synthetic stellar spectra is available from our websites ( http://www.iaa.csic.es/~rosa and http://www.astro.iag.usp.br/~lucimara/library.htm ).     

A comparative study of shallow groundwater level simulation with WA–ANN and ITS model in a coastal island of south China

Accurate and reliable prediction of shallow groundwater level is a critical component in water resources management. Two nonlinear models, WA–ANN method based on discrete wavelet transform (WA) and artificial neural network (ANN) and integrated time series (ITS) model, were developed to predict groundwater level fluctuations of a shallow coastal aquifer (Fujian Province, China). The two models were testified with the monitored groundwater level from 2000 to 2011. Two representative wells are selected with different locations within the study area. The error criteria were estimated using the coefficient of determination (R ²), Nash–Sutcliffe model efficiency coefficient (E), and root-mean-square error (RMSE). The best model was determined based on the RMSE of prediction using independent test data set. The WA–ANN models were found to provide more accurate monthly average groundwater level forecasts compared to the ITS models. The results of the study indicate the potential of WA–ANN models in forecasting groundwater levels. It is recommended that additional studies explore this proposed method, which can be used in turn to facilitate the development and implementation of more effective and sustainable groundwater management strategies.     

Object-based image analysis supported by data mining to discriminate large areas of soybean

This research aimed to analyze the possibility to estimate and automatically map large areas of soybean cultivation through the use of MODIS (Moderate-Resolution Imaging Spectroradiometer) images. Two major techniques were used: GEOgraphic-Object-Based Image Analysis (GEOBIA) and Data Mining (DM). In order to obtain the images, the segmentation algorithm implemented by Definiens Developer was used. A decision tree (DT) was created from a training set previously prepared. Time-series of images from the MODIS sensor aboard the Terra satellite were acquired in order to represent the wide variation of the vegetation pattern along the soybean crop cycle. The time-series data were used only for the CEI index. Furthermore, to compare the results obtained from GEOBIA, the slicing technique was used at the CEI level. After the training, the DT was applied to the vegetation indices generating the thematic map of the spatial distribution of soybean. In accordance with the error matrix and kappa parameter analysis, tests for statistical significance were created. Results indicate that the classification achieved by Kappa coefficients is 0.76. In short, the obtained results proved that combining vegetation indices and time-series data using GEOBIA return promising results for mapping soybean plantation on a regional scale.