1,823 research outputs found

    DataJoint: managing big scientific data using MATLAB or Python

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    The rise of big data in modern research poses serious challenges for data management: Large and intricate datasets from diverse instrumentation must be precisely aligned, annotated, and processed in a variety of ways to extract new insights. While high levels of data integrity are expected, research teams have diverse backgrounds, are geographically dispersed, and rarely possess a primary interest in data science. Here we describe DataJoint, an open-source toolbox designed for manipulating and processing scientific data under the relational data model. Designed for scientists who need a flexible and expressive database language with few basic concepts and operations, DataJoint facilitates multi-user access, efficient queries, and distributed computing. With implementations in both MATLAB and Python, DataJoint is not limited to particular file formats, acquisition systems, or data modalities and can be quickly adapted to new experimental designs. DataJoint and related resources are available at http://datajoint.github.com

    Killing Tensors and Conformal Killing Tensors from Conformal Killing Vectors

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    Koutras has proposed some methods to construct reducible proper conformal Killing tensors and Killing tensors (which are, in general, irreducible) when a pair of orthogonal conformal Killing vectors exist in a given space. We give the completely general result demonstrating that this severe restriction of orthogonality is unnecessary. In addition we correct and extend some results concerning Killing tensors constructed from a single conformal Killing vector. A number of examples demonstrate how it is possible to construct a much larger class of reducible proper conformal Killing tensors and Killing tensors than permitted by the Koutras algorithms. In particular, by showing that all conformal Killing tensors are reducible in conformally flat spaces, we have a method of constructing all conformal Killing tensors (including all the Killing tensors which will in general be irreducible) of conformally flat spaces using their conformal Killing vectors.Comment: 18 pages References added. Comments and reference to 2-dim case. Typos correcte

    Recombination rate and selection strength in HIV intra-patient evolution

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    The evolutionary dynamics of HIV during the chronic phase of infection is driven by the host immune response and by selective pressures exerted through drug treatment. To understand and model the evolution of HIV quantitatively, the parameters governing genetic diversification and the strength of selection need to be known. While mutation rates can be measured in single replication cycles, the relevant effective recombination rate depends on the probability of coinfection of a cell with more than one virus and can only be inferred from population data. However, most population genetic estimators for recombination rates assume absence of selection and are hence of limited applicability to HIV, since positive and purifying selection are important in HIV evolution. Here, we estimate the rate of recombination and the distribution of selection coefficients from time-resolved sequence data tracking the evolution of HIV within single patients. By examining temporal changes in the genetic composition of the population, we estimate the effective recombination to be r=1.4e-5 recombinations per site and generation. Furthermore, we provide evidence that selection coefficients of at least 15% of the observed non-synonymous polymorphisms exceed 0.8% per generation. These results provide a basis for a more detailed understanding of the evolution of HIV. A particularly interesting case is evolution in response to drug treatment, where recombination can facilitate the rapid acquisition of multiple resistance mutations. With the methods developed here, more precise and more detailed studies will be possible, as soon as data with higher time resolution and greater sample sizes is available.Comment: to appear in PLoS Computational Biolog

    DataJoint: managing big scientific data using MATLAB or Python

    Get PDF
    The rise of big data in modern research poses serious challenges for data management: Large and intricate datasets from diverse instrumentation must be precisely aligned, annotated, and processed in a variety of ways to extract new insights. While high levels of data integrity are expected, research teams have diverse backgrounds, are geographically dispersed, and rarely possess a primary interest in data science. Here we describe DataJoint, an open-source toolbox designed for manipulating and processing scientific data under the relational data model. Designed for scientists who need a flexible and expressive database language with few basic concepts and operations, DataJoint facilitates multi-user access, efficient queries, and distributed computing. With implementations in both MATLAB and Python, DataJoint is not limited to particular file formats, acquisition systems, or data modalities and can be quickly adapted to new experimental designs. DataJoint and related resources are available at http://datajoint.github.com

    Comparison of bacterial communities of conventional and A-stage activated sludge systems

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    The bacterial community structure of 10 different wastewater treatment systems and their influents has been investigated through pyrosequencing, yielding a total of 283486 reads. These bioreactors had different technological configurations: conventional activated sludge (CAS) systems and very highly loaded A-stage systems. A-stage processes are proposed as the first step in an energy producing municipal wastewater treatment process. Pyrosequencing analysis indicated that bacterial community structure of all influents was similar. Also the bacterial community of all CAS bioreactors was similar. Bacterial community structure of A-stage bioreactors showed a more case-specific pattern. A core of genera was consistently found for all influents, all CAS bioreactors and all A-stage bioreactors, respectively, showing that different geographical locations in The Netherlands and Spain did not affect the functional bacterial communities in these technologies. The ecological roles of these bacteria were discussed. Influents and A-stage bioreactors shared several core genera, while none of these were shared with CAS bioreactors communities. This difference is thought to reside in the different operational conditions of the two technologies. This study shows that bacterial community structure of CAS and A-stage bioreactors are mostly driven by solids retention time (SRT) and hydraulic retention time (HRT), as suggested by multivariate redundancy analysis.Department of Civil EngineeringInstitute of Water Research from the University of GranadaDepartment of Environmental Biotechnology of the Delft University of Technolog

    Measurement of the cross-section and charge asymmetry of WW bosons produced in proton-proton collisions at s=8\sqrt{s}=8 TeV with the ATLAS detector

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    This paper presents measurements of the W+μ+νW^+ \rightarrow \mu^+\nu and WμνW^- \rightarrow \mu^-\nu cross-sections and the associated charge asymmetry as a function of the absolute pseudorapidity of the decay muon. The data were collected in proton--proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS experiment at the LHC and correspond to a total integrated luminosity of 20.2~\mbox{fb^{-1}}. The precision of the cross-section measurements varies between 0.8% to 1.5% as a function of the pseudorapidity, excluding the 1.9% uncertainty on the integrated luminosity. The charge asymmetry is measured with an uncertainty between 0.002 and 0.003. The results are compared with predictions based on next-to-next-to-leading-order calculations with various parton distribution functions and have the sensitivity to discriminate between them.Comment: 38 pages in total, author list starting page 22, 5 figures, 4 tables, submitted to EPJC. All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2017-13

    The mitochondrial genome of Angiostrongylus mackerrasae as a basis for molecular, epidemiological and population genetic studies

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    BACKGROUND: Angiostrongylus mackerrasae is a metastrongyloid nematode endemic to Australia, where it infects the native bush rat, Rattus fuscipes. This lungworm has an identical life cycle to that of Angiostrongylus cantonensis, a leading cause of eosinophilic meningitis in humans. The ability of A. mackerrasae to infect non-rodent hosts, specifically the black flying fox, raises concerns as to its zoonotic potential. To date, data on the taxonomy, epidemiology and population genetics of A. mackerrasae are unknown. Here, we describe the mitochondrial (mt) genome of A. mackerrasae with the aim of starting to address these knowledge gaps. METHODS: The complete mitochondrial (mt) genome of A. mackerrasae was amplified from a single morphologically identified adult worm, by long-PCR in two overlapping amplicons (8 kb and 10 kb). The amplicons were sequenced using the MiSeq Illumina platform and annotated using an in-house pipeline. Amino acid sequences inferred from individual protein coding genes of the mt genomes were concatenated and then subjected to phylogenetic analysis using Bayesian inference. RESULTS: The mt genome of A. mackerrasae is 13,640 bp in size and contains 12 protein coding genes (cox1-3, nad1-6, nad4L, atp6 and cob), and two ribosomal RNA (rRNA) and 22 transfer RNA (tRNA) genes. CONCLUSIONS: The mt genome of A. mackerrasae has similar characteristics to those of other Angiostrongylus species. Sequence comparisons reveal that A. mackerrasae is closely related to A. cantonensis and the two sibling species may have recently diverged compared with all other species in the genus with a highly specific host selection. This mt genome will provide a source of genetic markers for explorations of the epidemiology, biology and population genetics of A. mackerrasae

    Search for chargino-neutralino production with mass splittings near the electroweak scale in three-lepton final states in √s=13 TeV pp collisions with the ATLAS detector

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    A search for supersymmetry through the pair production of electroweakinos with mass splittings near the electroweak scale and decaying via on-shell W and Z bosons is presented for a three-lepton final state. The analyzed proton-proton collision data taken at a center-of-mass energy of √s=13  TeV were collected between 2015 and 2018 by the ATLAS experiment at the Large Hadron Collider, corresponding to an integrated luminosity of 139  fb−1. A search, emulating the recursive jigsaw reconstruction technique with easily reproducible laboratory-frame variables, is performed. The two excesses observed in the 2015–2016 data recursive jigsaw analysis in the low-mass three-lepton phase space are reproduced. Results with the full data set are in agreement with the Standard Model expectations. They are interpreted to set exclusion limits at the 95% confidence level on simplified models of chargino-neutralino pair production for masses up to 345 GeV
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