216 research outputs found

    Entity linking of tweets based on dominant entity candidates

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    © 2018, Springer-Verlag GmbH Austria, part of Springer Nature. Entity linking, also known as semantic annotation, of textual content has received increasing attention. Recent works in this area have focused on entity linking on text with special characteristics such as search queries and tweets. The semantic annotation of tweets is specially proven to be challenging given the informal nature of the writing and the short length of the text. In this paper, we propose a method to perform entity linking on tweets built based on one primary hypothesis. We hypothesize that while there are formally many possible entity candidates for an ambiguous mention in a tweet, as listed on the disambiguation page of the corresponding entity on Wikipedia, there are only few entity candidates that are likely to be employed in the context of Twitter. Based on this hypothesis, we propose a method to identify such dominant entity candidates for each ambiguous mention and use them in the annotation process. Particularly, our proposed work integrates two phases (i) dominant entity candidate detection, which applies community detection methods for finding the dominant candidates of ambiguous mentions; and (ii) named entity disambiguation that links a tweet to entities in Wikipedia by only considering the identified dominant entity candidates. Our investigations show that: (1) there are only very few entity candidates for each ambiguous mention in a tweet that need to be considered when performing disambiguation. This helps us limit the candidate search space and hence noticeably reduce the entity linking time; (2) limiting the search space to only a subset of disambiguation options will not only improve entity linking execution time but will also lead to improved accuracy of the entity linking process when the main entity candidates of each mention are mined from a temporally aligned corpus. We show that our proposed method offers competitive results with the state-of-the-art methods in terms of precision and recall on widely used gold standard datasets while significantly reducing the time for processing each tweet

    Global Peak in Atmospheric Radiocarbon Provides a Potential Definition for the Onset of the Anthropocene Epoch in 1965.

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    Anthropogenic activity is now recognised as having profoundly and permanently altered the Earth system, suggesting we have entered a human-dominated geological epoch, the 'Anthropocene'. To formally define the onset of the Anthropocene, a synchronous global signature within geological-forming materials is required. Here we report a series of precisely-dated tree-ring records from Campbell Island (Southern Ocean) that capture peak atmospheric radiocarbon (14C) resulting from Northern Hemisphere-dominated thermonuclear bomb tests during the 1950s and 1960s. The only alien tree on the island, a Sitka spruce (Picea sitchensis), allows us to seasonally-resolve Southern Hemisphere atmospheric 14C, demonstrating the 'bomb peak' in this remote and pristine location occurred in the last-quarter of 1965 (October-December), coincident with the broader changes associated with the post-World War II 'Great Acceleration' in industrial capacity and consumption. Our findings provide a precisely-resolved potential Global Stratotype Section and Point (GSSP) or 'golden spike', marking the onset of the Anthropocene Epoch

    Nanoethics, science communication, and a fourth model for public engagement

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    This paper develops a fourth model of public engagement with science, grounded in the principle of nurturing scientific agency through online participatory bioethics. It argues that social media is an effective device through which to enable such engagement, as it has the capacity to empower users and transforms audiences into co-producers of knowledge, rather than consumers of content, the value of which is recognised within the citizen science movement. Social media also fosters greater engagement with the political and legal implications of science, thus promoting the value of scientific citizenship through the acquisition of science capital. This argument is explored by considering the case of nanoscience and nanotechnology, as an exemplar for how emerging technologies may be handled by the scientific community and science policy makers, and as a technology that has defined a second era of science communication

    Simulation of dimensionality effects in thermal transport

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    The discovery of nanostructures and the development of growth and fabrication techniques of one- and two-dimensional materials provide the possibility to probe experimentally heat transport in low-dimensional systems. Nevertheless measuring the thermal conductivity of these systems is extremely challenging and subject to large uncertainties, thus hindering the chance for a direct comparison between experiments and statistical physics models. Atomistic simulations of realistic nanostructures provide the ideal bridge between abstract models and experiments. After briefly introducing the state of the art of heat transport measurement in nanostructures, and numerical techniques to simulate realistic systems at atomistic level, we review the contribution of lattice dynamics and molecular dynamics simulation to understanding nanoscale thermal transport in systems with reduced dimensionality. We focus on the effect of dimensionality in determining the phononic properties of carbon and semiconducting nanostructures, specifically considering the cases of carbon nanotubes, graphene and of silicon nanowires and ultra-thin membranes, underlying analogies and differences with abstract lattice models.Comment: 30 pages, 21 figures. Review paper, to appear in the Springer Lecture Notes in Physics volume "Thermal transport in low dimensions: from statistical physics to nanoscale heat transfer" (S. Lepri ed.

    Cation–π interactions in protein–ligand binding: theory and data-mining reveal different roles for lysine and arginine

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    We have studied the cation–p interactions of neutral aromatic ligands with the cationic amino acid residues arginine, histidine and lysine using ab initio calculations, symmetry adapted perturbation theory (SAPT), and a systematic meta-analysis of all available Protein Data Bank (PDB) X-ray structures. Quantum chemical potential energy surfaces (PES) for these interactions were obtained at the DLPNO-CCSD(T) level of theory and compared against the empirical distribution of 2012 unique protein–ligand cation–π interactions found in X-ray crystal structures. We created a workflow to extract these structures from the PDB, filtering by interaction type and residue pKa. The gas phase cation–π interaction of lysine is the strongest by more than 10 kcal mol^-1, but the empirical distribution of 582 X-ray structures lies away from the minimum on the interaction PES. In contrast, 1381 structures involving arginine match the underlying calculated PES with good agreement. SAPT analysis revealed that underlying differences in the balance of electrostatic and dispersion contributions are responsible for this behavior in the context of the protein environment. The lysine–arene interaction, dominated by electrostatics, is greatly weakened by a surrounding dielectric medium and causes it to become essentially negligible in strength and without a well-defined equilibrium separation. The arginine–arene interaction involves a near equal mix of dispersion and electrostatic attraction, which is weakened to a much smaller degree by the surrounding medium. Our results account for the paucity of cation–π interactions involving lysine, even though this is a more common residue than arginine. Aromatic ligands are most likely to interact with cationic arginine residues as this interaction is stronger than for lysine in higher polarity surroundings

    Phrase embedding learning based on external and internal context with compositionality constraint

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    Different methods are proposed to learn phrase embedding, which can be mainly divided into two strands. The first strand is based on the distributional hypothesis to treat a phrase as one non-divisible unit and to learn phrase embedding based on its external context similar to learn word embedding. However, distributional methods cannot make use of the information embedded in component words and they also face data spareness problem. The second strand is based on the principle of compositionality to infer phrase embedding based on the embedding of its component words. Compositional methods would give erroneous result if a phrase is non-compositional. In this paper, we propose a hybrid method by a linear combination of the distributional component and the compositional component with an individualized phrase compositionality constraint. The phrase compositionality is automatically computed based on the distributional embedding of the phrase and its component words. Evaluation on five phrase level semantic tasks and experiments show that our proposed method has overall best performance. Most importantly, our method is more robust as it is less sensitive to datasets

    Aggregation and settling in aqueous polydisperse alumina nanoparticle suspensions

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    Nanoparticle suspensions (also called nanofluids) are often polydisperse and tend to settle with time. Settling kinetics in these systems are known to be complex and hence challenging to understand. In this work, polydisperse spherical alumina (Al2O3) nanoparticles in the size range of ~10-100nm were dispersed in water and examined for aggregation and settling behaviour near its isoelectric point (IEP). A series of settling experiments were conducted and the results were analysed by photography and by Small Angle X-ray Scattering (SAXS). The settling curve obtained from standard bed height measurement experiments indicated two different types of behaviour, both of which were also seen in the SAXS data. But the SAXS data were remarkably able to pick out the rapid settling regime as a result of the high temporal resolution (10s) used. By monitoring the SAXS intensity, it was further possible to record the particle aggregation process for the first time. Optical microscopy images were produced on drying and dried droplets extracted from the suspension at various times. Dried deposits showed the rapid decrease in the number of very large particles with time which qualitatively validates the SAXS prediction, and therefore its suitability as a tool to study unstable polydisperse colloids. Keywords: Nanoparticles, nanofluids, polydisperse, aggregation, settling, alumina, microscopy, SAX

    Phylogeography of a Land Snail Suggests Trans-Mediterranean Neolithic Transport

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    Background: Fragmented distribution ranges of species with little active dispersal capacity raise the question about their place of origin and the processes and timing of either range fragmentation or dispersal. The peculiar distribution of the land snail Tudorella sulcata s. str. in Southern France, Sardinia and Algeria is such a challenging case. Methodology: Statistical phylogeographic analyses with mitochondrial COI and nuclear hsp70 haplotypes were used to answer the questions of the species' origin, sequence and timing of dispersal. The origin of the species was on Sardinia. Starting from there, a first expansion to Algeria and then to France took place. Abiotic and zoochorous dispersal could be excluded by considering the species' life style, leaving only anthropogenic translocation as parsimonious explanation. The geographic expansion could be dated to approximately 8,000 years before present with a 95% confidence interval of 10,000 to 3,000 years before present. Conclusions: This period coincides with the Neolithic expansion in the Western Mediterranean, suggesting a role of these settlers as vectors. Our findings thus propose that non-domesticated animals and plants may give hints on the direction and timing of early human expansion routes

    Scrapheap Challenge: A novel bulk-bone metabarcoding method to investigate ancient DNA in faunal assemblages

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    Highly fragmented and morphologically indistinct fossil bone is common in archaeological and paleontological deposits but unfortunately it is of little use in compiling faunal assemblages. The development of a cost-effective methodology to taxonomically identify bulk bone is therefore a key challenge. Here, an ancient DNA methodology using high-throughput sequencing is developed to survey and analyse thousands of archaeological bones from southwest Australia. Fossils were collectively ground together depending on which of fifteen stratigraphical layers they were excavated from. By generating fifteen synthetic blends of bulk bone powder, each corresponding to a chronologically distinct layer, samples could be collectively analysed in an efficient manner. A diverse range of taxa, including endemic, extirpated and hitherto unrecorded taxa, dating back to c.46,000 years BP was characterized. The method is a novel, cost-effective use for unidentifiable bone fragments and a powerful molecular tool for surveying fossils that otherwise end up on the taxonomic “scrapheap”

    High recombination rates and hotspots in a Plasmodium falciparum genetic cross

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    Using the universal P2/P8 primers, we were able to obtain the gene segments of chromo-helicase-DNA binding protein (CHD)-Z and CHD-W from ten species of ardeid birds including Chinese egret (Egretta eulophotes), little egret (E. garzetta), eastern reef egret (E. sacra), great egret (Ardea alba), grey heron (A. cinerea), Chinese pond-heron (Ardeola bacchus), cattle egret (Bubulcus ibis), black-crowned night-heron (Nycticorax nycticorax), cinnamon bittern (Ixobrychus cinnamomeus) and yellow bittern (I. sinensis). Based on conserved regions inside the P2/P8-derived sequences, we designed new PCR primers for sex identification in these ardeid species. Using agarose gel electrophoresis, the PCR products showed two bands for females (140 bp derived from CHD-W and the other 250 bp from CHD-ZW), whereas the males showed only the 250 bp band. The results indicated that our new primers could be used for accurate and convenient sex identification in ardeid species.National Natural Science Foundation of China[30970380, 40876077]; Fujian Natural Science Foundation of China[2008S0007, 2009J01195
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