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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Callingham, J. R.; Shimwell, T. W.; Vedantham, H. K.; Bassa, C. G.; +43 Authors

    The LOFAR data in this manuscript were processed by the LOFAR Two-Metre Sky Survey (LoTSS) team. This team made use of the LOFAR direction-independent calibration pipeline (https://github.com/lofar-astron/prefactor), which was deployed by the LOFAR e-infragroup on the Dutch National Grid infrastructure with support of the SURF Co-operative through grants e-infra 160022 e-infra 160152 (Mechev et al. 2017). The LoTSS direction dependent calibration and imaging pipeline (http://github.com/mhardcastle/ddf-pipeline/) was run on compute clusters at Leiden Observatory and the University of Hertfordshire, which are supported by a European Research Council (ERC) Advanced Grant [NEWCLUSTERS-321271] and the UK Science and Technology Funding Council (STFC) [ST/P000096/1]. The Jülich LOFAR Long Term Archive and the German LOFAR network are both coordinated and operated by the Jülich Supercomputing Centre (JSC), and computing resources on the supercomputer JUWELS at JSC were provided by the Gauss Centre for Supercomputing e.V. (grant CHTB00) through the John von Neumann Institute for Computing (NIC). J.R.C. thanks the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO) for support via the Talent Programme Veni grant. H.K. and S.B. acknowledge funding from the NWO for the project e-MAPS (project number Vi.Vidi.203.093) under the NWO talent scheme VIDI. T.W.H.Y. acknowledges funding from EOSC Future (Grant Agreement no. 101017536) projects funded by the European Union’s Horizon 2020 research and innovation programme. P.N.B. is grateful for support from the UK STFC via grant ST/V000594/1. M.J.H. acknowledges support from the UK STFC [ST/V000624/1]. M.H. acknowledges funding from the ERC under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 772663). R.J.v.W. and R.T. acknowledge support from the ERC Starting Grant ClusterWeb 804208. G.J.W. gratefully acknowledges the support of an Emeritus Fellowship from The Leverhulme Trust. D.J.B. acknowledges funding from the German Science Foundation DFG, via the Collaborative Research Center SFB1491 “Cosmic Interacting Matters – From Source to Signal”. A. Bonafede, A. Botteon, D.N.H., and C.J.R. acknowledge support from ERC Stg DRA-NOEL n. 714245 and MIUR FARE grant “SMS”. A.D. acknowledges support by the BMBF Verbundforschung under the grant 05A20STA. K.L.E. is a Jan-sky Fellow of the National Radio Astronomy Observatory. M. Haj and K.C.H. acknowledge the MSHE for granting funds for the Polish contribution to the International LOFAR Telescope (MSHE decision no. DIR/WK/2016/2017/05-1) and for maintenance of the LOFAR PL-612 Baldy (MSHE decision no. 59/E-383/SPUB/SP/2019.1), and LOFAR PL-611 Lazy (MSHE decision no. 46/E-338/SPUB/SP/2019). M.K. acknowledges support from the German Science Foundation DFG, via the Research Unit FOR 5195 “Relativistic Jets in Active Galaxies”. M.K.B. acknowledges support from the National Science Centre, Poland under grant no. 2017/26/E/ST9/00216. B.M. acknowledges support from the UK STFC under grants ST/R00109X/1, ST/R000794/1, and ST/T000295/1. L.K.M. is grateful for support from the UKRI Future Leaders Fellowship (grant MR/T042842/1). D.G.N. acknowledges funding from Conicyt through Fondecyt Postdoctorado (project code 3220195). M.P.T. acknowledges financial support from the Spanish Ministerio de Ciencia e Innovación (MCIN), the Agencia Estatal de Investigación (AEI) through the “Center of Excellence Severo Ochoa” award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709) and through grant PID2020-117404GB-C21 funded by MCIN/AEI/10.13039/501100011033. T.P.R. acknowledges support from the ERC Grant No. 743029 (EASY). A.R. acknowledges funding from the NWO Aspasia grant (number: 015.016.033). M.V. acknowledges financial support from the Inter-University Institute for Data Intensive Astronomy (IDIA), a partnership of the University of Cape Town, the University of Pretoria, the University of the Western Cape and the South African Radio Astronomy Observatory, and from the South African Department of Science and Innovation’s National Research Foundation under the ISARP RADIOSKY2020 Joint Research Scheme (DSI-NRF Grant Number 113121) and the CSUR HIPPO Project (DSI-NRF Grant Number 121291). This research has made use of the SIMBAD database, operated at CDS, Strasbourg, France, and NASA’s Astrophysics Data System. This work has also made use of TOPCAT (Taylor 2005); the IPYTHON package (Pérez & Granger 2007); SciPy (Jones et al. 2001); MATPLOTLIB, a PYTHON library for publication quality graphics (Hunter 2007); ASTROPY, a community-developed core PYTHON package for astronomy (Astropy Collaboration 2013); and NUMPY (Van Der Walt et al. 2011). We present the detection of 68 sources from the most sensitive radio survey in circular polarisation conducted to date. We used the second data release of the 144 MHz LOFAR Two-metre Sky Survey to produce circularly polarised maps with a median noise of 140 µJy beam−1 and resolution of 20″ for ≈27% of the northern sky (5634 deg2). The leakage of total intensity into circular polarisation is measured to be ≈0.06%, and our survey is complete at flux densities ≥1 mJy. A detection is considered reliable when the circularly polarised fraction exceeds 1%. We find the population of circularly polarised sources is composed of four distinct classes: stellar systems, pulsars, active galactic nuclei, and sources unidentified in the literature. The stellar systems can be further separated into chromospherically active stars, M dwarfs, and brown dwarfs. Based on the circularly polarised fraction and lack of an optical counterpart, we show it is possible to infer whether the unidentified sources are likely unknown pulsars or brown dwarfs. By the completion of this survey of the northern sky, we expect to detect 300±100 circularly polarised sources. © The Authors 2023. Full list of authors: Callingham, J. R.; Shimwell, T. W.; Vedantham, H. K.; Bassa, C. G.; O'Sullivan, S. P.; Yiu, T. W. H.; Bloot, S.; Best, P. N.; Hardcastle, M. J.; Haverkorn, M.; Kavanagh, R. D.; Lamy, L.; Pope, B. J. S.; Rottgering, H. J. A.; Schwarz, D. J.; Tasse, C.; van Weeren, R. J.; White, G. J.; Zarka, P.; Bomans, D. J.; Bonafede, A.; Bonato, M.; Botteon, A.; Bruggen, M.; Chyzy, K. T.; Drabent, A.; Emig, K. L.; Gloudemans, A. J.; Guerkan, G.; Hajduk, M.; Hoang, D. N.; Hoeft, M.; Iacobelli, M.; Kadler, M.; Kunert-Bajraszewska, M.; Mingo, B.; Morabito, L. K.; Nair, D. G.; Perez-Torres, M.; Ray, T. P.; Riseley, C. J.; Rowlinson, A.; Shulevski, A.; Sweijen, F.; Timmerman, R.; Vaccari, M.; Zheng, J.-- This is an Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-S). Peer reviewed

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    Durham Research Online
    Article . 2023 . Peer-reviewed
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    https://doi.org/10.48550/arxiv...
    Article . 2022
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      Durham Research Online
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      https://doi.org/10.48550/arxiv...
      Article . 2022
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    Authors: Hube, Christoph; Fetahu, Besnik;

    Biased language commonly occurs around topics which are of controversial nature, thus, stirring disagreement between the different involved parties of a discussion. This is due to the fact that for language and its use, specifically, the understanding and use of phrases, the stances are cohesive within the particular groups. However, such cohesiveness does not hold across groups. In collaborative environments or environments where impartial language is desired (e.g. Wikipedia, news media), statements and the language therein should represent equally the involved parties and be neutrally phrased. Biased language is introduced through the presence of inflammatory words or phrases, or statements that may be incorrect or one-sided, thus violating such consensus. In this work, we focus on the specific case of phrasing bias, which may be introduced through specific inflammatory words or phrases in a statement. For this purpose, we propose an approach that relies on a recurrent neural networks in order to capture the inter-dependencies between words in a phrase that introduced bias. We perform a thorough experimental evaluation, where we show the advantages of a neural based approach over competitors that rely on word lexicons and other hand-crafted features in detecting biased language. We are able to distinguish biased statements with a precision of P=0.92, thus significantly outperforming baseline models with an improvement of over 30%. Finally, we release the largest corpus of statements annotated for biased language. The Twelfth ACM International Conference on Web Search and Data Mining, February 11--15, 2019, Melbourne, VIC, Australia

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    http://arxiv.org/pdf/1811.0574...
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    https://doi.org/10.1145/328960...
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      https://doi.org/10.1145/328960...
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    Authors: Callingham, J. R.; Shimwell, T. W.; Vedantham, H. K.; Bassa, C. G.; +43 Authors

    The LOFAR data in this manuscript were processed by the LOFAR Two-Metre Sky Survey (LoTSS) team. This team made use of the LOFAR direction-independent calibration pipeline (https://github.com/lofar-astron/prefactor), which was deployed by the LOFAR e-infragroup on the Dutch National Grid infrastructure with support of the SURF Co-operative through grants e-infra 160022 e-infra 160152 (Mechev et al. 2017). The LoTSS direction dependent calibration and imaging pipeline (http://github.com/mhardcastle/ddf-pipeline/) was run on compute clusters at Leiden Observatory and the University of Hertfordshire, which are supported by a European Research Council (ERC) Advanced Grant [NEWCLUSTERS-321271] and the UK Science and Technology Funding Council (STFC) [ST/P000096/1]. The Jülich LOFAR Long Term Archive and the German LOFAR network are both coordinated and operated by the Jülich Supercomputing Centre (JSC), and computing resources on the supercomputer JUWELS at JSC were provided by the Gauss Centre for Supercomputing e.V. (grant CHTB00) through the John von Neumann Institute for Computing (NIC). J.R.C. thanks the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO) for support via the Talent Programme Veni grant. H.K. and S.B. acknowledge funding from the NWO for the project e-MAPS (project number Vi.Vidi.203.093) under the NWO talent scheme VIDI. T.W.H.Y. acknowledges funding from EOSC Future (Grant Agreement no. 101017536) projects funded by the European Union’s Horizon 2020 research and innovation programme. P.N.B. is grateful for support from the UK STFC via grant ST/V000594/1. M.J.H. acknowledges support from the UK STFC [ST/V000624/1]. M.H. acknowledges funding from the ERC under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 772663). R.J.v.W. and R.T. acknowledge support from the ERC Starting Grant ClusterWeb 804208. G.J.W. gratefully acknowledges the support of an Emeritus Fellowship from The Leverhulme Trust. D.J.B. acknowledges funding from the German Science Foundation DFG, via the Collaborative Research Center SFB1491 “Cosmic Interacting Matters – From Source to Signal”. A. Bonafede, A. Botteon, D.N.H., and C.J.R. acknowledge support from ERC Stg DRA-NOEL n. 714245 and MIUR FARE grant “SMS”. A.D. acknowledges support by the BMBF Verbundforschung under the grant 05A20STA. K.L.E. is a Jan-sky Fellow of the National Radio Astronomy Observatory. M. Haj and K.C.H. acknowledge the MSHE for granting funds for the Polish contribution to the International LOFAR Telescope (MSHE decision no. DIR/WK/2016/2017/05-1) and for maintenance of the LOFAR PL-612 Baldy (MSHE decision no. 59/E-383/SPUB/SP/2019.1), and LOFAR PL-611 Lazy (MSHE decision no. 46/E-338/SPUB/SP/2019). M.K. acknowledges support from the German Science Foundation DFG, via the Research Unit FOR 5195 “Relativistic Jets in Active Galaxies”. M.K.B. acknowledges support from the National Science Centre, Poland under grant no. 2017/26/E/ST9/00216. B.M. acknowledges support from the UK STFC under grants ST/R00109X/1, ST/R000794/1, and ST/T000295/1. L.K.M. is grateful for support from the UKRI Future Leaders Fellowship (grant MR/T042842/1). D.G.N. acknowledges funding from Conicyt through Fondecyt Postdoctorado (project code 3220195). M.P.T. acknowledges financial support from the Spanish Ministerio de Ciencia e Innovación (MCIN), the Agencia Estatal de Investigación (AEI) through the “Center of Excellence Severo Ochoa” award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709) and through grant PID2020-117404GB-C21 funded by MCIN/AEI/10.13039/501100011033. T.P.R. acknowledges support from the ERC Grant No. 743029 (EASY). A.R. acknowledges funding from the NWO Aspasia grant (number: 015.016.033). M.V. acknowledges financial support from the Inter-University Institute for Data Intensive Astronomy (IDIA), a partnership of the University of Cape Town, the University of Pretoria, the University of the Western Cape and the South African Radio Astronomy Observatory, and from the South African Department of Science and Innovation’s National Research Foundation under the ISARP RADIOSKY2020 Joint Research Scheme (DSI-NRF Grant Number 113121) and the CSUR HIPPO Project (DSI-NRF Grant Number 121291). This research has made use of the SIMBAD database, operated at CDS, Strasbourg, France, and NASA’s Astrophysics Data System. This work has also made use of TOPCAT (Taylor 2005); the IPYTHON package (Pérez & Granger 2007); SciPy (Jones et al. 2001); MATPLOTLIB, a PYTHON library for publication quality graphics (Hunter 2007); ASTROPY, a community-developed core PYTHON package for astronomy (Astropy Collaboration 2013); and NUMPY (Van Der Walt et al. 2011). We present the detection of 68 sources from the most sensitive radio survey in circular polarisation conducted to date. We used the second data release of the 144 MHz LOFAR Two-metre Sky Survey to produce circularly polarised maps with a median noise of 140 µJy beam−1 and resolution of 20″ for ≈27% of the northern sky (5634 deg2). The leakage of total intensity into circular polarisation is measured to be ≈0.06%, and our survey is complete at flux densities ≥1 mJy. A detection is considered reliable when the circularly polarised fraction exceeds 1%. We find the population of circularly polarised sources is composed of four distinct classes: stellar systems, pulsars, active galactic nuclei, and sources unidentified in the literature. The stellar systems can be further separated into chromospherically active stars, M dwarfs, and brown dwarfs. Based on the circularly polarised fraction and lack of an optical counterpart, we show it is possible to infer whether the unidentified sources are likely unknown pulsars or brown dwarfs. By the completion of this survey of the northern sky, we expect to detect 300±100 circularly polarised sources. © The Authors 2023. Full list of authors: Callingham, J. R.; Shimwell, T. W.; Vedantham, H. K.; Bassa, C. G.; O'Sullivan, S. P.; Yiu, T. W. H.; Bloot, S.; Best, P. N.; Hardcastle, M. J.; Haverkorn, M.; Kavanagh, R. D.; Lamy, L.; Pope, B. J. S.; Rottgering, H. J. A.; Schwarz, D. J.; Tasse, C.; van Weeren, R. J.; White, G. J.; Zarka, P.; Bomans, D. J.; Bonafede, A.; Bonato, M.; Botteon, A.; Bruggen, M.; Chyzy, K. T.; Drabent, A.; Emig, K. L.; Gloudemans, A. J.; Guerkan, G.; Hajduk, M.; Hoang, D. N.; Hoeft, M.; Iacobelli, M.; Kadler, M.; Kunert-Bajraszewska, M.; Mingo, B.; Morabito, L. K.; Nair, D. G.; Perez-Torres, M.; Ray, T. P.; Riseley, C. J.; Rowlinson, A.; Shulevski, A.; Sweijen, F.; Timmerman, R.; Vaccari, M.; Zheng, J.-- This is an Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-S). Peer reviewed

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    Authors: Hube, Christoph; Fetahu, Besnik;

    Biased language commonly occurs around topics which are of controversial nature, thus, stirring disagreement between the different involved parties of a discussion. This is due to the fact that for language and its use, specifically, the understanding and use of phrases, the stances are cohesive within the particular groups. However, such cohesiveness does not hold across groups. In collaborative environments or environments where impartial language is desired (e.g. Wikipedia, news media), statements and the language therein should represent equally the involved parties and be neutrally phrased. Biased language is introduced through the presence of inflammatory words or phrases, or statements that may be incorrect or one-sided, thus violating such consensus. In this work, we focus on the specific case of phrasing bias, which may be introduced through specific inflammatory words or phrases in a statement. For this purpose, we propose an approach that relies on a recurrent neural networks in order to capture the inter-dependencies between words in a phrase that introduced bias. We perform a thorough experimental evaluation, where we show the advantages of a neural based approach over competitors that rely on word lexicons and other hand-crafted features in detecting biased language. We are able to distinguish biased statements with a precision of P=0.92, thus significantly outperforming baseline models with an improvement of over 30%. Finally, we release the largest corpus of statements annotated for biased language. The Twelfth ACM International Conference on Web Search and Data Mining, February 11--15, 2019, Melbourne, VIC, Australia

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