In this paper we present a study of chemical abundances in six star-forming regions. Stellar parameters and metallicities are derived using high-resolution, high S/N spectra of weak-line T-Tauri stars in each region. The results show that nearby star-forming regions have a very small abundance dispersion (only 0.033 dex in [Fe/H]). The average metallicity found is slightly below that of the Sun, although compatible with solar once the errors are taken into account. The derived abundances for Si and Ni show that the observed stars have the abundances typical of Galactic thin disk stars of the same metallicity. The impact of these observations is briefly discussed in the context of the Galactic chemical evolution, local inter-stellar medium abundances, and in the origin of metal-rich stars in the solar neighbourhood (namely, stars more likely to harbour planets). The implication for future planet-search programmes around very young, nearby stars is also discussed.

Novelty search is a state-of-the-art evolutionary approach that promotes behavioural novelty instead of pursuing a static objective. Along with a large number of successful applications, many different variants of novelty search have been proposed. It is still unclear, however, how some key parameters and algorithmic components influence the evolutionary dynamics and performance of novelty search. In this paper, we conduct a comprehensive empirical study focused on novelty search's algorithmic components. We study the k parameter -the number of nearest neighbours used in the computation of novelty scores; the use and function of an archive; how to combine novelty search with fitness-based evolution; and how to configure the mutation rate of the underlying evolutionary algorithm. Our study is conducted in a simulated maze navigation task. Our results show that the configuration of novelty search can have a significant impact on performance and behaviour space exploration. We conclude with a number of guidelines for the implementation and configuration of novelty search, which should help future practitioners to apply novelty search more effectively.

We report the discovery of a peculiar L dwarf from the UKIDSS Large Area Survey (LAS), ULAS J222711−004547. The very red infrared photometry (MKO J − K = 2.79±0.06, WISE W 1−W 2 = 0.65±0.05) of ULAS J222711−004547 makes it one of the reddest brown dwarfs discovered so far. We obtained a moderate resolution spectrum of this target using VLT/XSHOOTER, and classify it as L7pec, confirming its very red nature. Comparison to theoretical models suggests that the object could be a low-gravity L dwarf with a solar or higher than solar metallicity. Nonetheless, the match of such fits to the spectral energy distribution is rather poor and this and other less red peculiar red L dwarfs pose new challenges for the modeling of ultracool atmospheres, especially to the understanding of the effects of condensates and their sensitivity to gravity and metallicity. We determined the proper motion of ULAS J222711−004547 using the data available in the literature, and we find that its kinematics do not suggest membership of any of the known young associations. We show that applying a simple de-reddening curve to its spectrum allows it to resemble the spectra of the L7 spectroscopic standards without any spectral features that distinguish it as low metallicity or low gravity. Given the negligible interstellar reddening of the field containing our target, we conclude that the reddening of the spectrum is mostly due to an excess of dust in the photosphere of the target. De-reddening the spectrum using extinction curves for different dust species gives surprisingly good results and suggests a characteristic grain size of ∼0.5 µm. We show that by increasing the optical depth, the same extinction curves allow the spectrum of ULAS J222711−004547 to resemble the spectra of unusually blue L dwarfs and even slightly metal-poor L dwarfs. Grains of similar size also yield very good fits when dereddening other unusually red L dwarfs in the L5 to L7.5 range. These results suggest that the diversity in near infrared colours and spectra seen in late-L dwarfs could be due to differences in the optical thickness of the dust cloud deck.

We have conducted a search for L subdwarf candidates within the photometric catalogues of the UKIRT Infrared Deep Sky Survey and Sloan Digital Sky Survey. Six of our candidates are confirmed as L subdwarfs spectroscopically at optical and/or nearinfrared wavelengths. We also present new optical spectra of three previously known L subdwarfs (WISEA J001450.17-083823.4, 2MASS J00412179+3547133 and ULAS J124425.75+102439.3). We examined the spectral type and metallicity classification of subclasses of known L subdwarfs. We summarized the spectroscopic properties of L subdwarfs with different spectral types and subclasses. We classify these new L subdwarfs by comparing their spectra to known L subdwarfs and L dwarf standards. We estimate temperatures and metallicities of 22 late-type M and L subdwarfs by comparing their spectra to BT-Settl models. We find that L subdwarfs have temperatures between 1500 and 2700 K, which are higher than similar-typed L dwarfs by around 100-400 K depending on different subclasses and subtypes. We constrained the metallicity ranges of subclasses of M, L, and T subdwarfs. We also discussed the spectral-type and absolute magnitude relationships for L and T subdwarfs.

Swarm robotics is a promising approach for the coordination of large numbers of robots. While previous studies have shown that evolutionary robotics techniques can be applied to obtain robust and efficient self-organized behaviors for robot swarms, most studies have been conducted in simulation, and the few that have been conducted on real robots have been confined to laboratory environments. In this paper, we demonstrate for the first time a swarm robotics system with evolved control successfully operating in a real and uncontrolled environment. We evolve neural network-based controllers in simulation for canonical swarm robotics tasks, namely homing, dispersion, clustering, and monitoring. We then assess the performance of the controllers on a real swarm of up to ten aquatic surface robots. Our results show that the evolved controllers transfer successfully to real robots and achieve a performance similar to the performance obtained in simulation. We validate that the evolved controllers display key properties of swarm intelligence-based control, namely scalability, flexibility, and robustness on the real swarm. We conclude with a proof-of-concept experiment in which the swarm performs a complete environmental monitoring task by combining multiple evolved controllers.

The definitive version can be found at: http://onlinelibrary.wiley.com/ Copyright The Royal Astronomical SocietyWe present near-infrared photometry and spectroscopy, and warm-Spitzer IRAC photometry of the young very cool T dwarf Ross 458C, which we have typed as T8.5p. By applying the fiducial age constraints (<= 1 Gyr) imposed by the properties of the active M dwarf Ross 458A, we have used these data to determine that Ross 458C has T-eff = 695 +/- 60 K, log g = 4.0-4.7 and an inferred mass of 5-20M(J). We have compared fits of the near-infrared spectrum and IRAC photometry to the BT Settl and Saumon & Marley model grids, and have found that both sets provide best fits that are consistent with our derived properties, whilst the former provide a marginally closer match to the data for all scenarios explored here. The main difference between the model grids arises in the 4.5-mu m region, where the BT Settl models are able to better predict the flux through the IRAC filter, suggesting that non-equilibrium effects on the CO-CO2 ratio are important for shaping the mid-infrared spectra of very cool T dwarfs. We have also revisited the issue of the dust opacity in the spectra of Ross 458C that was raised by Burgasser et al. We have found that the BT Settl models which also incorporate a condensate cloud model provide a better match to the near-infrared spectrum of this target than the Saumon & Marley model with f(sed) = 2 and we briefly discuss the influence of condensate clouds on T dwarf spectra

Novelty search is a recent artificial evolution technique that challenges traditional evolutionary approaches. In novelty search, solutions are rewarded based on their novelty, rather than their quality with respect to a predefined objective. The lack of a predefined objective precludes premature convergence caused by a deceptive fitness function. In this paper, we apply novelty search combined with NEAT to the evolution of neural controllers for homogeneous swarms of robots. Our empirical study is conducted in simulation, and we use a common swarm robotics task -aggregation, and a more challenging task -sharing of an energy recharging station. Our results show that novelty search is unaffected by deception, is notably effective in bootstrapping the evolution, can find solutions with lower complexity than fitness-based evolution, and can find a broad diversity of solutions for the same task. Even in non-deceptive setups, novelty search achieves solution qualities similar to those obtained in traditional fitness-based evolution. Our study also encompasses variants of novelty search that work in concert with fitness-based evolution to combine the exploratory character of novelty search with the exploitatory character of objective-based evolution. We show that these variants can further improve the performance of novelty search. Overall, our study shows that novelty search is a promising alternative for the evolution of controllers for robotic swarms.In this section, we first discuss swarm robotics and evolutionary robotics, and the main challenges associated with these fields. We then present novelty search and how it can overcome some of these challenges. We go on to review recently proposed variants of novelty search. We conclude the section with a description of NEAT, the neuroevolution method used in our experiments.

We have searched the Wide‐field Infrared Survey Explorer first data release for widely separated (≤10 000 au) late T dwarf companions to Hipparcos and Gliese stars. We have discovered a new binary system containing a K‐band suppressed T8p dwarf WISEP J142320.86+011638.1 and the mildly metal poor ([Fe/H] =−0.38 ± 0.06) primary BD +01° 2920 (HIP 70319), a G1 dwarf at a distance of 17.2 pc. This new benchmark has Teff= 680 ± 55 K and a mass of 20–50MJup. Its spectral properties are well modelled except for known discrepancies in the Y and K bands. Based on the well‐determined metallicity of its companion, the properties of BD +01° 2920B imply that the currently known T dwarfs are dominated by young low‐mass objects. We also present an accurate proper motion for the T8.5 dwarf WISEP J075003.84+272544.8.