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The authors also acknowledge the support and collaboration of many other colleagues in their respective institutes, research communities and IT Infrastructures, together with the funding received by these from many different sources. These include but are not limited to the following: (i) The Worldwide LHC Computing Grid (WLCG) project is a global collaboration of more than 170 computing centres in 43 countries, linking up national and international grid infrastructures. Funding is acknowledged from many national funding bodies and we acknowledge the support of several operational infrastructures including EGI, OSG and NDGF/NeIC. (ii) EGI acknowledges the funding and support received from the European Commission and the many National Grid Initiatives and other members. EOSC-hub receives funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 777536. (iii) The work leading to these results has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 730941 (AARC2). (iv) Work on the development of ESGF's identity management system has been supported by The UK Natural Environment Research Council and funding from the European Union's Seventh Framework Programme for research, technological development and demonstration through projects IS-ENES (grant agreement no 228203) and IS-ENES2 (grant agreement no 312979). (v) Ludek Matyska and Michal Prochazka acknowledge funding from the RI ELIXIR CZ project funded by MEYS Czech Republic No. LM2015047. (vi) Scott Koranda acknowledges support provided by the United States National Science Foundation under Grant No. PHY-1700765. (vii) GÉANT Association on behalf of the GN4 Phase 2 project (GN4-2).The research leading to these results has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 731122(GN4-2). (viii) ELIXIR acknowledges support from Research Infrastructure programme of Horizon 2020 grant No 676559 EXCELERATE. (ix) CORBEL life science cluster acknowledges support from Horizon 2020 research and innovation programme under grant agreement No 654248. (x) Mirjam van Daalen acknowledges that the research leading to this result has been supported by the project CALIPSOplus under the Grant Agreement 730872 from the EU Framework Programme for Research and Innovation HORIZON 2020. (xi) EISCAT is an international association supported by research organisations in China (CRIRP), Finland (SA), Japan (NIPR), Norway (NFR), Sweden (VR), and the United Kingdom (NERC). This white-paper expresses common requirements of Research Communities seeking to leverage Identity Federation for Authentication and Authorisation. Recommendations are made to Stakeholders to guide the future evolution of Federated Identity Management in a direction that better satisfies research use cases. The authors represent research communities, Research Services, Infrastructures, Identity Federations and Interfederations, with a joint motivation to ease collaboration for distributed researchers. The content has been edited collaboratively by the Federated Identity Management for Research (FIM4R) Community, with input sought at conferences and meetings in Europe, Asia and North America.

AbstractIntroductionMaternal characteristics and mother–adolescent relationships are thought to affect the emotional development of adolescents. Adolescents can learn to regulate their emotions by observing their mothers, and this is further facilitated by maternal autonomy support. Therefore, this study longitudinally examined the associations among maternal emotion dysregulation, maternal autonomy support, and adolescent emotion dysregulation.MethodParticipants were 466 Dutch adolescents (54.51% males; Mage = 14.03, SD = 0.45) and 462 mothers (Mage = 45.49, SD = 4.47), who completed self‐reports of emotion dysregulation and maternal autonomy support for five consecutive years.ResultsRandom Intercept‐Cross Lagged Panel Model analyses showed that at the between‐family level, maternal emotion dysregulation was correlated with adolescent emotion dysregulation, adolescent‐reported maternal autonomy support, and mother‐reported maternal autonomy support; and adolescent emotion dysregulation was correlated with adolescent‐reported maternal autonomy support. At the within‐family level, higher than usual maternal emotion dysregulation was positively related to adolescent emotion dysregulation at Time 1, yet, was negatively related to adolescent emotion dysregulation at other time points concurrently, and predicted lower adolescent emotion dysregulation in the next year. Also, higher than usual adolescent emotion dysregulation was related to lower adolescent‐reported maternal autonomy support both concurrently and the next year.ConclusionsBoth mothers and adolescents played an important role in adolescent emotional development. To promote adolescent emotional development, it is important to target both maternal emotion dysregulation to understand the development of adolescent emotion dysregulation, and adolescent emotion dysregulation to prevent mothers from providing less autonomy support to their adolescents.

Gender bias in machine translation can manifest when choosing gender inflections based on spurious gender correlations. For example, always translating doctors as men and nurses as women. This can be particularly harmful as models become more popular and deployed within commercial systems. Our work presents the largest evidence for the phenomenon in more than 19 systems submitted to the WMT over four diverse target languages: Czech, German, Polish, and Russian. To achieve this, we use WinoMT, a recent automatic test suite which examines gender coreference and bias when translating from English to languages with grammatical gender. We extend WinoMT to handle two new languages tested in WMT: Polish and Czech. We find that all systems consistently use spurious correlations in the data rather than meaningful contextual information. Comment: Accepted WMT20