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The Darkweb is highly popular and widely used for several types of cybercrime. Darkweb marketplaces in particular, are meeting places that provide anonymity, illegal product and service variety, and ease of use. Botmasters can utilize these platforms to acquire the necessary components needed to set up and maintain a botnet infrastructure, but also provide their services to clients. Since botnets can also be viewed from a business perspective, these components can be characterized as elements of a business model, each associated with a different botnet set of activities. In this paper, we crawl 26 marketplace and with focus on botnet-related listings form a dataset of 36,314 listings, along with 1,163 vendors. We present our aggregated findings in regard to marketplace characteristics, listings, and vendors. Additionally, we utilize the botnet Value Chain Model to correlate the targeted listings to specific model segments. With this approach we gain insight on how the business model relates to the botnet market in real time, and what significance this holds from a botmaster's point of view. Our results suggest that botmasters have a wide variety of options on all of the activities related to the botnet setup, maintenance, and revenue generation, all available within the marketplaces, at quite low prices. Lastly, we utilize the usernames and PGP keys of the vendors, in an effort to detect their potential cross-platform activity throughout the 26 platforms.

Multilingualism is a cultural cornerstone of Europe and firmly anchored in the European treaties including full language equality. However, language barriers impacting business, cross-lingual and cross-cultural communication are still omnipresent. Language Technologies (LTs) are a powerful means to break down these barriers. While the last decade has seen various initiatives that created a multitude of approaches and technologies tailored to Europe's specific needs, there is still an immense level of fragmentation. At the same time, AI has become an increasingly important concept in the European Information and Communication Technology area. For a few years now, AI, including many opportunities, synergies but also misconceptions, has been overshadowing every other topic. We present an overview of the European LT landscape, describing funding programmes, activities, actions and challenges in the different countries with regard to LT, including the current state of play in industry and the LT market. We present a brief overview of the main LT-related activities on the EU level in the last ten years and develop strategic guidance with regard to four key dimensions. Proceedings of the 12th Language Resources and Evaluation Conference (LREC 2020). To appear

As the second decade of the twenty-first century closes, challenges to human rights have deepened. Democracy is under stress, cultural battles within states have become heightened, and strongman politics are on the rise. Contemporary and historical reflections on rights are perhaps more pressing than ever – projects this book takes on via plain-language forms blending academic and commentary-based styles.

The incorporation of algorithmic procedures into the automation of image production has been gradual, but has reached critical mass over the past century, especially with the advent of photography, the introduction of digital computers and the use of artificial intelligence (AI) and machine learning (ML). Due to the increasingly significant influence algorithmic processes have on visual media, there has been an expansion of the possibilities as to how images may behave, and a consequent struggle to define them. This algorithmic turn highlights inner tensions within existing notions of the image, namely raising questions regarding the autonomy of machines, author- and viewer- ship, and the veracity of representations. In this sense, algorithmic images hover uncertainly between human and machine as producers and interpreters of visual information, between representational and non-representational, and between visible surface and the processes behind it. This paper gives an introduction to fundamental internal discrepancies which arise within algorithmically produced images, examined through a selection of relevant artistic examples. Focusing on the theme of uncertainty, this investigation considers how algorithmic images contain aspects which conflict with the certitude of computation, and how this contributes to a difficulty in defining images.

Being at the Western fringe of Europe, Iberia had a peculiar prehistory and a complex pattern of Neolithization. A few studies, all based on modern populations, reported the presence of DNA of likely African origin in this region, generally concluding it was the result of recent gene flow, probably during the Islamic period. Here we provide evidence of much older gene flow from Africa to Iberia by sequencing whole genomes from four human remains from Northern Portugal and Southern Spain dated around 4,000 years BP (from the Middle Neolithic to the Bronze Age). We found one of them to carry an unequivocal Sub-Saharan mitogenome of most likely West or West-Central African origin, never reported before in prehistoric remains outside Africa. Our analyses of ancient nuclear genomes show small but significant levels of Sub-Saharan African affinity in several ancient Iberian samples, which indicates that what we detected was not an occasional individual phenomenon, but an admixture event recognizable at the population level. We interpret this result as evidence of an early migration process from Africa into the Iberian Peninsula through a Western route, possibly across the Strait of Gibraltar. Alignment_ancient_phylogenyAlignment of complete mitogenome sequences for ancient phylogeny (related to Figure 2)Alignment_modern_phylogenyAlingment of mitogenome sequences for modern phylogeny (related to Supplementary Figure S5)

This project was set out to explore the role of the Turing Test in the development of Artificial Intelligence (AI), with emphasis on the historical perspective. This report contains an introductory presentation of the Turing Test and Artificial Intelligence. Furthermore, it presents two methods for analysis. The first method is a quantitative search in extracting the number of results from Google Scholars for search range between 1950 and 2019. The searched terms are ‘Turing Test’ and ‘Artificial Intelligence’. The second method is the one used for the analysis of two case studies, ELIZA and Google Duplex. In exploring the historical development, ELIZA is an early research topic from 1966 and Google Duplex is a contemporary project from 2018. This report concludes that the Turing Test appears to have played a role in the historical development of AI. Results from the quantitative search show that there is an exponential growth, followed by a short stabilisation, before it begins to decay towards the last decade. Both case studies failed when subjected to a strict Turing Test. Though when subjected to the Total Turing Test, Google Duplex seems to surpass it. Finally, this report also concludes that the Turing Test may no longer be relevant, as mediums for AI have evolved beyond text-based and most developments are no longer concerned with tricking humans.

In the paper we describe a new EU infrastructure project dedicated to lexicography. The project is part of the Horizon 2020 program, with a duration of four years (2018-2022). The result of the project will be an infrastructure which will (1) enable efficient access to high quality lexicographic data, and (2) bridge the gap between more advanced and less-resourced scholarly communities working on lexicographic resources. One of the main issues addressed by the project is the fact that current lexicographic resources have different levels of (incompatible) structuring, and are not equally suitable for application in in Natural Language Processing and other fields. The project will therefore develop strategies, tools and standards for extracting, structuring and linking lexicographic resources to enable their inclusion in Linked Open Data and the Semantic Web, as well as their use in the context of digital humanities.

The extent of gene flow during the range expansion of non-native species influences the amount of genetic diversity retained in expanding populations. Here, we analyse the population genetic structure of the raccoon dog (Nyctereutes procyonoides) in north-eastern and central Europe. This invasive species is of management concern because it is highly susceptible to fox rabies and an important secondary host of the virus. We hypothesized that the large number of introduced animals and the species’ dispersal capabilities led to high population connectivity and maintenance of genetic diversity throughout the invaded range. We genotyped 332 tissue samples from seven European countries using 16 microsatellite loci. Different algorithms identified three genetic clusters corresponding to Finland, Denmark and a large ‘central’ population that reached from introduction areas in western Russia to northern Germany. Cluster assignments provided evidence of long-distance dispersal. The results of an Approximate Bayesian Computation analysis supported a scenario of equal effective population sizes among different pre-defined populations in the large central cluster. Our results are in line with strong gene flow and secondary admixture between neighbouring demes leading to reduced genetic structuring, probably a result of its fairly rapid population expansion after introduction. The results presented here are remarkable in the sense that we identified a homogenous genetic cluster inhabiting an area stretching over more than 1500km. They are also relevant for disease management, as in the event of a significant rabies outbreak, there is a great risk of a rapid virus spread among raccoon dog populations. genetic_dataFile with individual ID, population, geographical coordinates, microsatellite genotypes at 16 loci