9 research outputs found

    Evaluation of a proposal for reliable low-cost grid power with 100% wind, water, and solar

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    A number of analyses, meta-Analyses, and assessments, including those performed by the Intergovernmental Panel on Climate Change, the National Oceanic and Atmospheric Administration, the National Renewable Energy Laboratory, and the International Energy Agency, have concluded that deployment of a diverse portfolio of clean energy technologies makes a transition to a low-carbon-emission energy system both more feasible and less costly than other pathways. In contrast, Jacobson et al. [Jacobson MZ, Delucchi MA, Cameron MA, Frew BA (2015) Proc Natl Acad Sci USA 112(49):15060-15065] argue that it is feasible to provide low-cost solutions to the grid reliability problem with 100% penetration of WWS [wind, water and solar power] across all energy sectors in the continental United States between 2050 and 2055 , with only electricity and hydrogen as energy carriers. In this paper, we evaluate that study and find significant shortcomings in the analysis. In particular, we point out that this work used invalid modeling tools, contained modeling errors, and made implausible and inadequately supported assumptions. Policy makers should treat with caution any visions of a rapid, reliable, and low-cost transition to entire energy systems that relies almost exclusively on wind, solar, and hydroelectric power

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

    Climate: More ways to govern geoengineering

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    Measurement of D+(s) and D*+(s) production in B meson decays and from continuum e+ e- annihilations at s**(1/2) = 10.6-GeV.

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    none622Bernard Aubert; D. Boutigny; J.M. Gaillard; A. Hicheur; Y. Karyotakis; J.P. Lees; P. Robbe; V. Tisserand; A. Palano; G.P. Chen; J.C. Chen; N.D. Qi; G. Rong; P. Wang; Y.S. Hz; G. Eigen; P.L. Reinertsen; B. Stugu; B. Abbott; G.S. Abrams; A.W. Borgland; A.B. Breon; David Nathan Brown; Janice Button-Shafer; R.N. Cahn; A.R. Clark; M.S. Gill; A.V. Gritsan; Y. Groysman; R.G. Jacobsen; R.W. Kadel; J. Kadyk; L.T. Kerth; S. Kluth; Yu.G. Kolomensky; J.F. Kral; C. LeClerc; M.E. Levi; T. Liu; G. Lynch; A.B. Meyer; M. Momayezi; P.J. Oddone; A. Perazzo; M. Pripstein; N.A. Roe; A. Romosan; M.T. Ronan; V.G. Shelkov; A.V. Telnov; W.A. Wenzel; P.G. Bright-Thomas; T.J. Harrison; C.M. Hawkes; D.J. Knowles; S.W. O'Neale; R.C. Penny; A.T. Watson; N.K Watson; T. Deppermann; K. Goetzen; H. Koch; J. Krug; M. Kunze; B. Lewandowski; K. Peters; H. Schmuecker; M. Steinke; J.C. Andress; N.R. Barlow; W. Bhimji; N. Chevalier; P.J. Clark; W.N. Cottingham; N. De Groot; N. Dyce; B. Foster; J.D. McFall; D. 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L., Kocian; Urs, Langenegger; David W. G. S., Leith; S., Luitz; V., Luth; H. L., Lynch; H., Marsiske; S., Menke; R., Messner; K. C., Moffeit; R., Mount; D. R., Muller; C. P., O'Grady; M., Perl; S., Petrak; Helen R., Quinn; B. N., Ratcliff; S. H., Robertson; L. S., Rochester; A., Roodman; T., Schietinger; R. H., Schindler; J., Schwiening; V. V., Serbo; A., Snyder; A., Soha; S. M., Spanier; J., Stelzer; D., Su; M. K., Sullivan; H. A., Tanaka; J., Va'Vra; S. R., Wagner; A. J. R., Weinstein; William J., Wisniewski; D. H., Wright; C. C., Young; P. R., Burchat; C. H., Cheng; David P., Kirkby; T. I., Meyer; C., Roat; R., Henderson; W., Bugg; H., Cohn; A. W., Weidemann; J. M., Izen; I., Kitayama; X. C., Lou; M., Turcotte; F., Bianchi; Marcella, Bona; B., Di Girolamo; D., Gamba; A., Smol; D., Zanin; L., Bosisio; G., Della Ricca; L., Lanceri; A., Pompili; P., Poropat; M., Prest; E., Vallazza; G., Vuagnin; R. S., Panvini; C., Brown; Asoka S., De Silva; Robert V., Kowalewski; J. M., Roney; H. R., Band; E., Charles; S., Dasu; F., Di Lodovico; A. M., Eichenbaum; H., Hu; J. R., Johnson; R., Liu; J., Nielsen; Y., Pan; R., Prepost; I. J., Scott; J. H., von Wimmersperg Toeller; S. L., Wu; Z., Yu; H., Zobernig; T. M. B., Kordich; H., Nea

    Evolution of genes and genomes on the Drosophila phylogeny

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    Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species

    TRY plant trait database, enhanced coverage and open access

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    Plant traits-the morphological, ahawnatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives
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