Predicting spectral features in galaxy spectra from broad-band photometry

We explore the prospects of predicting emission-line features present in galaxy spectra given broad-band photometry alone. There is a general consent that colours, and spectral features, most notably the 4000 angstrom break, can predict many properties of galaxies, including star formation rates and hence they could infer some of the line properties. We argue that these techniques have great prospects in helping us understand line emission in extragalactic objects and might speed up future galaxy redshift surveys if they are to target emission-line objects only. We use two independent methods, Artificial Neural Networks (based on the ANNz code) and Locally Weighted Regression (LWR), to retrieve correlations present in the colour N-dimensional space and to predict the equivalent widths present in the corresponding spectra. We also investigate how well it is possible to separate galaxies with and without lines from broad-band photometry only. We find, unsurprisingly, that recombination lines can be well predicted by galaxy colours. However, among collisional lines some can and some cannot be predicted well from galaxy colours alone, without any further redshift information. We also use our techniques to estimate how much information contained in spectral diagnostic diagrams can be recovered from broad-band photometry alone. We find that it is possible to classify active galactic nuclei and star formation objects relatively well using colours only. We suggest that this technique could be used to considerably improve redshift surveys such as the upcoming Fibre Multi Object Spectrograph (FMOS) survey and the planned Wide Field Multi Object Spectrograph (WFMOS) survey.

Evolutionary patterns in neotropical Helieae (Gentianaceae): evidence from morphology, chloroplast and nuclear DNA sequences

Parsimony-based phylogenetic analyses of the neotropical tribe Helieae (Gentianaceae) are presented, including 22 of the 23 genera and 60 species. This study is based on data from morphology, palynology, and seed micromorphology (127 structural characters), and DNA sequences (matK, trnL intron, ITS). Phylogenetic reconstructions based on ITS and morphology provided the greatest resolution, morphological data further helping to tentatively place several taxa for which DNA was not available (Celiantha, Lagenanthus, Rogersonanthus, Roraimaea, Senaea, Sipapoantha, Zonanthus). Celiantha, Prepusa and Senaea together appear as the sister clade to the rest of Helieae. The remainder of Helieae is largely divided into two large subclades, the Macrocarpaea subclade and the Symbolanthus subclade. The first subclade includes Macrocarpaea, sister to Chorisepalum, Tochia, and Zonanthus. Irlbachia and Neblinantha are placed as sisters to the Symbolanthus subclade, which includes Aripuana, Calolisianthus, Chelonanthus, Helia, Lagenanthus, Lehmanniella, Purdieanthus, Rogersonanthus, Roraimaea, Sipapoantha, and symbolanthus. Generic-level polyphyly is detected in Chelonanthus and Irlbachia. Evolution of morphological characters is discussed, and new pollen and seed characters are evaluated for the first time in a combined morphological-molecular phylogenetic analysis.

Catalytic properties of thimet oligopeptidase H600A mutant

Thimet oligopeptidase (EC 3.4.24.15, TOP) is a metallo-oligopeptidase that participates in the intracellular metabolism of peptides. Predictions based on structurally analogous peptidases (Dcp and ACE-2) show that TOP can present a hinge-bend movement during substrate hydrolysis, what brings some residues closer to the substrate. One of these residues that in TOP crystallographic structure are far from the catalytic residues, but, moves toward the substrate considering this possible structural reorganization is His(600). In the present work, the role of His(600) of TOP was investigated by site-directed mutagenesis. TOP H600A mutant was characterized through analysis of S(1) and S(1)`, specificity, pH-activity profile and inhibition by JA-2. Results showed that TOP His(600) residue makes important interactions with the substrate, supporting the prediction that His(600) moves toward the substrate due to a hinge movement similar to the Dcp and ACE-2. Furthermore, the mutation H600A affected both K(m) and k(cat), showing the importance of His(600) for both substrate binding and/or product release from active site. Changes in the pH-profile may indicate also the participation of His(600) in TOP catalysis, transferring a proton to the newly generated NH(2)-terminus or helping Tyr(605) and/or Tyr(612) in the intermediate oxyanion stabilization. (C) 2010 Elsevier Inc. All rights reserved.

Evolutionary model trees for handling continuous classes in machine learning

Model trees are a particular case of decision trees employed to solve regression problems. They have the advantage of presenting an interpretable output, helping the end-user to get more confidence in the prediction and providing the basis for the end-user to have new insight about the data, confirming or rejecting hypotheses previously formed. Moreover, model trees present an acceptable level of predictive performance in comparison to most techniques used for solving regression problems. Since generating the optimal model tree is an NP-Complete problem, traditional model tree induction algorithms make use of a greedy top-down divide-and-conquer strategy, which may not converge to the global optimal solution. In this paper, we propose a novel algorithm based on the use of the evolutionary algorithms paradigm as an alternate heuristic to generate model trees in order to improve the convergence to globally near-optimal solutions. We call our new approach evolutionary model tree induction (E-Motion). We test its predictive performance using public UCI data sets, and we compare the results to traditional greedy regression/model trees induction algorithms, as well as to other evolutionary approaches. Results show that our method presents a good trade-off between predictive performance and model comprehensibility, which may be crucial in many machine learning applications. (C) 2010 Elsevier Inc. All rights reserved.

Investigation of the CO tolerance mechanism at several Pt-based bimetallic anode electrocatalysts in a PEM fuel cell

The electrocatalysis of CO tolerance of Pt/C, PtRu/C, PtFe/C, PtMo/C, and PtW/C at a PEM fuel cell anode has been investigated using single cell polarization and online electrochemical mass spectrometry (EMS) measurements, and cyclic voltammetry, X-ray diffraction (XRD), in situ X-ray absorption near edge structure (XANES) analyses of the electrocatalysts. For all bimetallic electrocatalysts, which presented higher CO tolerance, EMS results have shown that the production of CO(2) start at lower hydrogen electrode overpotentials as compared to Pt/C, confirming the occurrence of the so-called bifunctional mechanism. On the other hand, XANES results indicate an increase in the Pt 5d-band vacancies for the bimetallic catalysts, particulary for PtFe/C, this leading to a weakening of the Pt-CO bond, helping to increase the CO tolerance (the so-called electronic effect). For PtMo/C and PtRu/C supplied with H(2)/CO, the formation of CO(2) is observed even when the cell is at open circuit, confirming some elimination of CO by a chemical process, most probably the water gas shift reaction. (C) 2008 Elsevier Ltd. All rights reserved.