Seasonal variation in the copepod community structure from a tropical Amazon estuary, Northern Brazil

O presente estudo teve como objetivo principal avaliar a variação sazonal na estrutura da comunidade dos copépodos durante os meses de julho, setembro e novembro de 2003 (período seco) e janeiro, março e maio de 2004 (período chuvoso) no estuário do Curuçá, Norte do Brasil. As amostras foram coletadas nas marés de quadratura com auxílio de uma rede de plâncton com 200µm de abertura de malha, rebocada por meio de uma pequena embarcação a motor. As medidas de condutividade da água foram realizadas in situ utilizando-se um condutivímetro eletrônico e a salinidade foi posteriormente obtida através da transformação dos valores de condutividade. Os valores de salinidade variaram sazonalmente de 7, 2 ± 0, 1a 39, 2 ± 1, 8 (média ± desvio padrão), tendo sido principalmente influenciados pelas diferenças nas taxas de precipitação entre os períodos de amostragem estudados. Foram identificados no total 30 táxons, com Acartia tonsa constituindo a espécie mais representativa durante todo o período de estudo,seguida por Acartia lilljeborgii, Subeucalanus pileatus e Paracalanus quasimodo. Durante este trabalho, os valores de densidade, índices ecológicos e dominância das espécies de copépodos apresentaram um padrão sazonal claro, mostrando que a área estudada pode ser considerada sazonalmente heterogênea em relação a estes parâmetros investigados.

Insights into the morphology of the Serra da Cangalha impact structure from geophysical modeling

Forward modeling is commonly applied to gravity field data of impact structures to determine the main gravity anomaly sources. In this context, we have developed 2.5-D gravity models of the Serra da Cangalha impact structure for the purpose of investigating geological bodies/structures underneath the crater. Interpretation of the models was supported by ground magnetic data acquired along profiles, as well as by high resolution aeromagnetic data. Ground magnetic data reveal the presence of short-wavelength anomalies probably related to shallow magnetic sources that could have been emplaced during the cratering process. Aeromagnetic data show that the basement underneath the crater occurs at an average depth of about 1.9 km, whereas in the region beneath the central uplift it is raised to 0.51 km below the current surface. These depths are also supported by 2.5-D gravity models showing a gentle relief for the basement beneath the central uplift area. Geophysical data were used to provide further constraints for numeral modeling of crater formation that provided important information on the structural modification that affected the rocks underneath the crater, as well as on shock-induced modifications of target rocks. The results showed that the morphology is consistent with the current observations of the crater and that Serra da Cangalha was formed by a meteorite of approximately 1.4 km diameter striking at 12 km s-1.

Registration of Sub-Sequence and Multi-Camera Reconstructions for Camera Motion Estimation

This paper presents different application scenarios for which the registration of sub-sequence reconstructions or multi-camera reconstructions is essential for successful camera motion estimation and 3D reconstruction from video. The registration is achieved by merging unconnected feature point tracks between the reconstructions. One application is drift removal for sequential camera motion estimation of long sequences. The state-of-the-art in drift removal is to apply a RANSAC approach to find unconnected feature point tracks. In this paper an alternative spectral algorithm for pairwise matching of unconnected feature point tracks is used. It is then shown that the algorithms can be combined and applied to novel scenarios where independent camera motion estimations must be registered into a common global coordinate system. In the first scenario multiple moving cameras, which capture the same scene simultaneously, are registered. A second new scenario occurs in situations where the tracking of feature points during sequential camera motion estimation fails completely, e.g., due to large occluding objects in the foreground, and the unconnected tracks of the independent reconstructions must be merged. In the third scenario image sequences of the same scene, which are captured under different illuminations, are registered. Several experiments with challenging real video sequences demonstrate that the presented techniques work in practice.

Constraining planet structure from stellar chemistry: the cases of CoRoT-7, Kepler-10, and Kepler-93

Aims. We explore the possibility that the stellar relative abundances of different species can be used to constrain the bulk abundances of known transiting rocky planets. Methods. We use high resolution spectra to derive stellar parameters and chemical abundances for Fe, Si, Mg, O, and C in three stars hosting low mass, rocky planets: CoRoT-7, Kepler-10, and Kepler-93. These planets follow the same line along the mass-radius diagram, pointing toward a similar composition. The derived abundance ratios are compared with the solar values. With a simple stoichiometric model, we estimate the iron mass fraction in each planet, assuming stellar composition. Results. We show that in all cases, the iron mass fraction inferred from the mass-radius relationship seems to be in good agreement with the iron abundance derived from the host star's photospheric composition. Conclusions. The results suggest that stellar abundances can be used to add constraints on the composition of orbiting rocky planets.

Learning 3D structure from 2D images using LBP features

An automatic machine learning strategy for computing the 3D structure of monocular images from a single image query using Local Binary Patterns is presented. The 3D structure is inferred through a training set composed by a repository of color and depth images, assuming that images with similar structure present similar depth maps. Local Binary Patterns are used to characterize the structure of the color images. The depth maps of those color images with a similar structure to the query image are adaptively combined and filtered to estimate the final depth map. Using public databases, promising results have been obtained outperforming other state-of-the-art algorithms and with a computational cost similar to the most efficient 2D-to-3D algorithms.

Spatial network surrogates for disentangling complex system structure from spatial embedding of nodes

ACKNOWLEDGMENTS MW and RVD have been supported by the German Federal Ministry for Education and Research (BMBF) via the Young Investigators Group CoSy-CC2 (grant no. 01LN1306A). JFD thanks the Stordalen Foundation and BMBF (project GLUES) for financial support. JK acknowledges the IRTG 1740 funded by DFG and FAPESP. MT Gastner is acknowledged for providing his data on the airline, interstate, and Internet network. P Menck thankfully provided his data on the Scandinavian power grid. We thank S Willner on behalf of the entire zeean team for providing the data on the world trade network. All computations have been performed using the Python package pyunicorn [41] that is available at https://github.com/pik-copan/pyunicorn.

Removal of the N-linked glycan structure from the peanut peroxidase prxPNC2: Influence on protein stability and activity

Lines of transgenic tobacco have been generated that are transformed with either the wild-type peanut peroxidase prxPNC2 cDNA, driven by the CaMV3 5S promoter (designated 35S::prxPNC2-WT) or a mutated PNC2 cDNA in which the asparagine residue (Asn(189)) associated with the point of glycan attachment (Asn(189)) has been replaced with alanine (designated 35S::prxPNC2-M). PCR, using genomic DNA as template, has confirmed the integration of the 35S::prxPNC2-WT and 35::prxPNC2-M constructs into the tobacco genome, and western analysis using anti-PNC2 antibodies has revealed that the prxPNC2-WT protein product (PNC2-WT) accumulates with a molecular mass of 34,670 Da, while the prxPNC2-M protein product (PNC2-M) accumulates with a molecular mass of 32,600 Da. Activity assays have shown that both PNC2-WT and PNC2-M proteins accumulate preferentially in the ionically-bound cell wall fraction, with a significantly higher relative accumulation of the PNC2-WT isoenzyme in the ionically-bound fraction when compared with the PNC2-M isoform. Kinetic analysis of the partially purified PNC2-WT isozyme revealed an affinity constant (apparent K-m) of 11.2 mM for the reductor substrate guaiacol and 1.29 mM for H2O2, while values of 11.9 mM and 1.12 mM were determined for the PNC2-M isozyme. A higher Arrenhius activation energy (E,,) was determined for the PNC2-M isozyme (22.9 kJ mol(-1)), when compared with the PNC2-WT isozyme (17.6 kJ mol(-1)), and enzyme assays have determined that the absence of the glycan influences the thermostability of the PNC2-M isozyme. These results are discussed with respect to the proposed roles of N-linked glycans attached to plant peroxidases. (c) 2005 Elsevier Ltd. All rights reserved.

Artefactual structure from least squares multidimensional scaling

We consider the problem of illusory or artefactual structure from the visualisation of high-dimensional structureless data. In particular we examine the role of the distance metric in the use of topographic mappings based on the statistical field of multidimensional scaling. We show that the use of a squared Euclidean metric (i.e. the SSTRESs measure) gives rise to an annular structure when the input data is drawn from a high-dimensional isotropic distribution, and we provide a theoretical justification for this observation.

Development of a probabilistic graphical structure from a model of mental health clinical expertise

This thesis explores the process of developing a principled approach for translating a model of mental-health risk expertise into a probabilistic graphical structure. Probabilistic graphical structures can be a combination of graph and probability theory that provide numerous advantages when it comes to the representation of domains involving uncertainty, domains such as the mental health domain. In this thesis the advantages that probabilistic graphical structures offer in representing such domains is built on. The Galatean Risk Screening Tool (GRiST) is a psychological model for mental health risk assessment based on fuzzy sets. In this thesis the knowledge encapsulated in the psychological model was used to develop the structure of the probability graph by exploiting the semantics of the clinical expertise. This thesis describes how a chain graph can be developed from the psychological model to provide a probabilistic evaluation of risk that complements the one generated by GRiST’s clinical expertise by the decomposing of the GRiST knowledge structure in component parts, which were in turned mapped into equivalent probabilistic graphical structures such as Bayesian Belief Nets and Markov Random Fields to produce a composite chain graph that provides a probabilistic classification of risk expertise to complement the expert clinical judgements

Artefactual structure from topographic mappings

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