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Abstract Background Hunter-gatherer lifestyles dominated the southern African landscape up to ~ 2000 years ago, when herding and farming groups started to arrive in the area. First, herding and livestock, likely of East African origin, appeared in southern Africa, preceding the arrival of the large-scale Bantu-speaking agro-pastoralist expansion that introduced West African-related genetic ancestry into the area. Present-day Khoekhoe-speaking Namaqua (or Nama in short) pastoralists show high proportions of East African admixture, linking the East African ancestry with Khoekhoe herders. Most other historical Khoekhoe populations have, however, disappeared over the last few centuries and their contribution to the genetic structure of present-day populations is not well understood. In our study, we analyzed genome-wide autosomal and full mitochondrial data from a population who trace their ancestry to the Khoekhoe-speaking Hessequa herders from the southern Cape region of what is now South Africa. Results We generated genome-wide data from 162 individuals and mitochondrial DNA data of a subset of 87 individuals, sampled in the Western Cape Province, South Africa, where the Hessequa population once lived. Using available comparative data from Khoe-speaking and related groups, we aligned genetic date estimates and admixture proportions to the archaeological proposed dates and routes for the arrival of the East African pastoralists in southern Africa. We identified several Afro-Asiatic-speaking pastoralist groups from Ethiopia and Tanzania who share high affinities with the East African ancestry present in southern Africa. We also found that the East African pastoralist expansion was heavily male-biased, akin to a pastoralist migration previously observed on the genetic level in ancient Europe, by which Pontic-Caspian Steppe pastoralist groups represented by the Yamnaya culture spread across the Eurasian continent during the late Neolithic/Bronze Age. Conclusion We propose that pastoralism in southern Africa arrived through male-biased migration of an East African Afro-Asiatic-related group(s) who introduced new subsistence and livestock practices to local southern African hunter-gatherers. Our results add to the understanding of historical human migration and mobility in Africa, connected to the spread of food-producing and livestock practices.

Review: Axel Hörstedt. Latin Dissertations and Disputations in the Early Modern Swedish Gymnasium: A Study of a Latin School Tradition c. 1620–c. 1820. Göteborgs universitet (PhD diss.), 2018, 502 pp.

This paper demonstrates a method to transform and link textual information scraped from companies' websites to the scientific body of knowledge. The method illustrates the benefit of Natural Language Processing (NLP) in creating links between established economic classification systems with novel and agile constructs that new data sources enable. Therefore, we experimented on the European classification of economic activities (known as NACE) on sectoral and company levels. We established a connection with Microsoft Academic Graph hierarchical topic modeling based on companies' website content. Central to the operationalization of our method are a web scraping process, NLP and a data transformation/linkage procedure. The method contains three main steps: data source identification, raw data retrieval, and data preparation and transformation. These steps are applied to two distinct data sources.

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.

A neural language model trained on a text corpus can be used to induce distributed representations of words, such that similar words end up with similar representations. If the corpus is multilingual, the same model can be used to learn distributed representations of languages, such that similar languages end up with similar representations. We show that this holds even when the multilingual corpus has been translated into English, by picking up the faint signal left by the source languages. However, just as it is a thorny problem to separate semantic from syntactic similarity in word representations, it is not obvious what type of similarity is captured by language representations. We investigate correlations and causal relationships between language representations learned from translations on one hand, and genetic, geographical, and several levels of structural similarity between languages on the other. Of these, structural similarity is found to correlate most strongly with language representation similarity, whereas genetic relationships—a convenient benchmark used for evaluation in previous work—appears to be a confounding factor. Apart from implications about translation effects, we see this more generally as a case where NLP and linguistic typology can interact and benefit one another.

AbstractThousands of Roma were killed in Ukraine by the Nazis and auxiliary police on the spot. There are more than 50,000 Roma in today’s Ukraine, represented by second and third generation decendants of the genocide survivors. The discussion on Roma identity cannot be isolated from the memory of the genocide, which makes the struggle over the past a reflexive landmark that mobilizes the Roma movement. About twenty Roma genocide memorials have been erected in Ukraine during last decade, and in 2016 the national memorial of the Roma genocide was opened in Babi Yar. However, scholars do not have a clear picture of memory narratives and memory practices of the Roma genocide in Ukraine. A comprehensive analysis of the contemporary situation is not possible without an examination of the history and memory of the Roma genocide before 1991.