Remote sensing as an aid for marsh management: Lafouche parish, Louisiana

NASA aerial photography, primarily color infrared and color positive transparencies, was used in a study of marsh management practices and in comparing managed and unmanaged marsh areas. Weir locations for tidal control are recommended

High-fidelity view of the structure and fragmentation of the high-mass, filamentary IRDC G11.11-0.12

Star formation in molecular clouds is intimately linked to their internal mass distribution. We present an unprecedentedly detailed analysis of the column density structure of a high-mass, filamentary molecular cloud, namely IRDC G11.11-0.12 (G11). We use two novel column density mapping techniques: high-resolution (FWHM=2", or ~0.035 pc) dust extinction mapping in near- and mid-infrared, and dust emission mapping with the Herschel satellite. These two completely independent techniques yield a strikingly good agreement, highlighting their complementarity and robustness. We first analyze the dense gas mass fraction and linear mass density of G11. We show that G11 has a top heavy mass distribution and has a linear mass density (M_l ~ 600 Msun pc^{-1}) that greatly exceeds the critical value of a self-gravitating, non-turbulent cylinder. These properties make G11 analogous to the Orion A cloud, despite its low star-forming activity. This suggests that the amount of dense gas in molecular clouds is more closely connected to environmental parameters or global processes than to the star-forming efficiency of the cloud. We then examine hierarchical fragmentation in G11 over a wide range of size-scales and densities. We show that at scales 0.5 pc > l > 8 pc, the fragmentation of G11 is in agreement with that of a self-gravitating cylinder. At scales smaller than l < 0.5 pc, the results agree better with spherical Jeans' fragmentation. One possible explanation for the change in fragmentation characteristics is the size-scale-dependent collapse time-scale that results from the finite size of real molecular clouds: at scales l < 0.5 pc, fragmentation becomes sufficiently rapid to be unaffected by global instabilities.Comment: 8 pages, 8 figures, accepted to A&

Understanding cellular function and disease with comparative pathway analysis

Pathway analysis is important in interpreting the functional implications of high-throughput experimental results, but robust comparison across platforms and species is problematic. A new approach, Pathprinting, provides a cross-platform, cross-species comparative analysis of pathway expression signatures. This method calculates pathway-level statistics from gene expression across nearly 180,000 microarrays in the Gene Expression Omnibus. Pathprinting can accurately retrieve phenotypically similar samples and identify sets of human and mouse genes that are prognostic in cancer

Cap And Trade Allowance Accounting: A Divergence Between Theory And Practice

This study concerns one of the most significant and glaring divergences between theory and practice that has emerged since the accounting discipline&rsquo;s conceptual framework was developed in the late 1970s.&nbsp; Through an extensive empirical examination of extant practices with respect to cap and trade allowances allotted to U.S. electric utilities under the Clean Air Act Amendments of 1990, this research demonstrates a surprising&mdash;and possibly unsupportable&mdash;divergence between expected and actual practice.&nbsp; The results of this research show that practice and theory diverge in a substantial and negative way.&nbsp; EPA-issued emissions allowances meet the accepted definition of an economic resource that will provide a future benefit, i.e., an asset.&nbsp; Yet, examination of five years&rsquo; of public financial disclosures for the entities affected by the CAAA shows scant recognition for the acquisition, disposition, or year-end existence of these tradable emissions permits.&nbsp; Financial statement users and other stakeholders of the affected entities may be seriously misled by the failure to recognize the allowances.&nbsp; This divergence between theory and practice does not appear to be justifiable

Bayesian and Maximum Likelihood Phylogenetic Analyses of Protein Sequence Data Under Relative Branch-Length Differences and Model Violation

Background: Bayesian phylogenetic inference holds promise as an alternative to maximum likelihood, particularly for large molecular-sequence data sets. We have investigated the performance of Bayesian inference with empirical and simulated protein-sequence data under conditions of relative branch-length differences and model violation. Results: With empirical protein-sequence data, Bayesian posterior probabilities provide more-generous estimates of subtree reliability than does the nonparametric bootstrap combined with maximum likelihood inference, reaching 100% posterior probability at bootstrap proportions around 80%. With simulated 7-taxon protein-sequence datasets, Bayesian posterior probabilities are somewhat more generous than bootstrap proportions, but do not saturate. Compared with likelihood, Bayesian phylogenetic inference can be as or more robust to relative branch-length differences for datasets of this size, particularly when among-sites rate variation is modeled using a gamma distribution. When the (known) correct model was used to infer trees, Bayesian inference recovered the (known) correct tree in 100% of instances in which one or two branches were up to 20-fold longer than the others. At ratios more extreme than 20-fold, topological accuracy of reconstruction degraded only slowly when only one branch was of relatively greater length, but more rapidly when there were two such branches. Under an incorrect model of sequence change, inaccurate trees were sometimes observed at less extreme branch-length ratios, and (particularly for trees with single long branches) such trees tended to be more inaccurate. The effect of model violation on accuracy of reconstruction for trees with two long branches was more variable, but gamma-corrected Bayesian inference nonetheless yielded more-accurate trees than did either maximum likelihood or uncorrected Bayesian inference across the range of conditions we examined. Assuming an exponential Bayesian prior on branch lengths did not improve, and under certain extreme conditions significantly diminished, performance. The two topology-comparison metrics we employed, edit distance and Robinson-Foulds symmetric distance, yielded different but highly complementary measures of performance. Conclusions: Our results demonstrate that Bayesian inference can be relatively robust against biologically reasonable levels of relative branch-length differences and model violation, and thus may provide a promising alternative to maximum likelihood for inference of phylogenetic trees from protein-sequence data

Bayesian and maximum likelihood phylogenetic analyses of protein sequence data under relative branch-length differences and model violation

BACKGROUND: Bayesian phylogenetic inference holds promise as an alternative to maximum likelihood, particularly for large molecular-sequence data sets. We have investigated the performance of Bayesian inference with empirical and simulated protein-sequence data under conditions of relative branch-length differences and model violation. RESULTS: With empirical protein-sequence data, Bayesian posterior probabilities provide more-generous estimates of subtree reliability than does the nonparametric bootstrap combined with maximum likelihood inference, reaching 100% posterior probability at bootstrap proportions around 80%. With simulated 7-taxon protein-sequence datasets, Bayesian posterior probabilities are somewhat more generous than bootstrap proportions, but do not saturate. Compared with likelihood, Bayesian phylogenetic inference can be as or more robust to relative branch-length differences for datasets of this size, particularly when among-sites rate variation is modeled using a gamma distribution. When the (known) correct model was used to infer trees, Bayesian inference recovered the (known) correct tree in 100% of instances in which one or two branches were up to 20-fold longer than the others. At ratios more extreme than 20-fold, topological accuracy of reconstruction degraded only slowly when only one branch was of relatively greater length, but more rapidly when there were two such branches. Under an incorrect model of sequence change, inaccurate trees were sometimes observed at less extreme branch-length ratios, and (particularly for trees with single long branches) such trees tended to be more inaccurate. The effect of model violation on accuracy of reconstruction for trees with two long branches was more variable, but gamma-corrected Bayesian inference nonetheless yielded more-accurate trees than did either maximum likelihood or uncorrected Bayesian inference across the range of conditions we examined. Assuming an exponential Bayesian prior on branch lengths did not improve, and under certain extreme conditions significantly diminished, performance. The two topology-comparison metrics we employed, edit distance and Robinson-Foulds symmetric distance, yielded different but highly complementary measures of performance. CONCLUSIONS: Our results demonstrate that Bayesian inference can be relatively robust against biologically reasonable levels of relative branch-length differences and model violation, and thus may provide a promising alternative to maximum likelihood for inference of phylogenetic trees from protein-sequence data

Integrating hierarchical controlled vocabularies with OWL ontology: A case study from the domain of molecular interactions

Many efforts at standardising terminologies within the biological domain have resulted in the construction of hierarchical controlled vocabularies that capture domain knowledge. Vocabularies, such as the PSI-MI vocabulary, capture both deep and extensive domain knowledge, in the OBO (Open Biomedical Ontologies) format. However hierarchical vocabularies, such as PSI-MI which are represented in OBO, only represent simple parent-child relationships between terms. By contrast, ontologies constructed using the Web Ontology Language (OWL), such as BioPax, define many richer types of relationships between terms. OWL provides a semantically rich structured language for expressing classes and sub-classes of entities and properties, relationships between them and domain-specific rules or axioms that can be applied to extract new information through semantic inferencing. In order to fully exploit the domain knowledge inherent in domain-specific controlled vocabularies, they need to be represented as OWL-DL ontologies, rather than in formats such as OBO. In this paper, we describe a method for converting OBO vocabularies into OWL and class instances represented as OWL-RDF triples. This approach preserves the hierarchical arrangement of the domain knowledge whilst also making the underlying parent-child relationships available to inferencing engines. This approach also has clear advantages over existing methods which incorporate terms from external controlled vocabularies as literals stripped of the context associated with their place in the hierarchy. By preserving this context, we enable machine inferencing over the ordered domain knowledge captured in OBO controlled vocabularie

Mycorrhizae Indirectly Enhance Competitive Effects of an Invasive Forb on a Native Bunchgrass

Mycorrhizae are important mediators of plant competition, but little is known about the role of mycorrhizae in the intense competitive effects that exotic plants can have on native species. In the greenhouse, we tested the effect of arbuscular mycorrhizal (AM) fungi on interspecific competition between Centaurea maculosa and Festuca idahoensis, on intraspecific competition between individuals of both species, and the growth of C. maculosa with either inorganic or organic phosphorus. Mycorrhizae had no direct effect on either species, but mycorrhizae increased C. maculosa\u27s negative effect on F. idahoensis. When competing with C. maculosa, nonmycorrhizal F. idahoensis were 171% larger than they were when mycorrhizae were present. In a second experiment, C. maculosa grown with larger F. idahoensis were 66% larger, in the presence of AM fungi, than when AM fungi were absent. Centaurea maculosa biomass was not affected by AM fungi, in either phosphorus treatment, in the absence of F. idahoensis. Root:shoot ratios differed between phosphorus treatments, but this difference seemed to be a result of slower growth in the organic phosphorus treatment. Our results were unusual in that the direct effects of mycorrhizae on both species were weak, but the indirect effect of AM fungi on the interactions between C. maculosa and F. idahoensis was strong. Our results suggest that AM fungi strongly enhance the ability of C. maculosa to invade native grasslands of western North America

Kinematic structure of massive star-forming regions - I. Accretion along filaments

The mid- and far-infrared view on high-mass star formation, in particular with the results from the Herschel space observatory, has shed light on many aspects of massive star formation. However, these continuum studies lack kinematic information. We study the kinematics of the molecular gas in high-mass star-forming regions. We complemented the PACS and SPIRE far-infrared data of 16 high-mass star-forming regions from the Herschel key project EPoS with N2H+ molecular line data from the MOPRA and Nobeyama 45m telescope. Using the full N2H+ hyperfine structure, we produced column density, velocity, and linewidth maps. These were correlated with PACS 70micron images and PACS point sources. In addition, we searched for velocity gradients. For several regions, the data suggest that the linewidth on the scale of clumps is dominated by outflows or unresolved velocity gradients. IRDC18454 and G11.11 show two velocity components along several lines of sight. We find that all regions with a diameter larger than 1pc show either velocity gradients or fragment into independent structures with distinct velocities. The velocity profiles of three regions with a smooth gradient are consistent with gas flows along the filament, suggesting accretion flows onto the densest regions. We show that the kinematics of several regions have a significant and complex velocity structure. For three filaments, we suggest that gas flows toward the more massive clumps are present.Comment: accepted by A&

Automatic, context-specific generation of Gene Ontology slims

Background: The use of ontologies to control vocabulary and structure annotation has added value to genome-scale data, and contributed to the capture and re-use of knowledge across research domains. Gene Ontology (GO) is widely used to capture detailed expert knowledge in genomic-scale datasets and as a consequence has grown to contain many terms, making it unwieldy for many applications. To increase its ease of manipulation and efficiency of use, subsets called GO slims are often created by collapsing terms upward into more general, high-level terms relevant to a particular context. Creation of a GO slim currently requires manipulation and editing of GO by an expert (or community) familiar with both the ontology and the biological context. Decisions about which terms to include are necessarily subjective, and the creation process itself and subsequent curation are time-consuming and largely manual