1,272 research outputs found
European wildcat populations are subdivided into five main biogeographic groups: consequences of Pleistocene climate changes or recent anthropogenic fragmentation?
Extant populations of the European wildcat are fragmented across the continent, the likely consequence of recent extirpations due to habitat loss and over-hunting. However, their underlying phylogeographic history has never been reconstructed. For testing the hypothesis that the European wildcat survived the Ice Age fragmented in Mediterranean refuges, we assayed the genetic variation at 31 microsatellites in 668 presumptive European wildcats sampled in 15 European countries. Moreover, to evaluate the extent of subspecies/population divergence and identify eventual wild Ă domestic cat hybrids, we genotyped 26 African wildcats from Sardinia and North Africa and 294 random-bred domestic cats. Results of multivariate analyses and Bayesian clustering confirmed that the European wild and the domestic cats (plus the African wildcats) belong to two well-differentiated clusters (average Ф ST = 0.159, r st = 0.392, P > 0.001; Analysis of molecular variance [AMOVA]). We identified from c. 5% to 10% cryptic hybrids in southern and central European populations. In contrast, wild-living cats in Hungary and Scotland showed deep signatures of genetic admixture and introgression with domestic cats. The European wildcats are subdivided into five main genetic clusters (average Ф ST = 0.103, r st = 0.143, P > 0.001; AMOVA) corresponding to five biogeographic groups, respectively, distributed in the Iberian Peninsula, central Europe, central Germany, Italian Peninsula and the island of Sicily, and in north-eastern Italy and northern Balkan regions (Dinaric Alps). Approximate Bayesian Computation simulations supported late Pleistocene-early Holocene population splittings (from c. 60 k to 10 k years ago), contemporary to the last Ice Age climatic changes. These results provide evidences for wildcat Mediterranean refuges in southwestern Europe, but the evolution history of eastern wildcat populations remains to be clarified. Historical genetic subdivisions suggest conservation strategies aimed at enhancing gene flow through the restoration of ecological corridors within each biogeographic units. Concomitantly, the risk of hybridization with free-ranging domestic cats along corridor edges should be carefully monitored
Flows of people in villages and large centres in Bronze Age Italy through strontium and oxygen isotopes
This study investigates to what extent Bronze Age societies in Northern Italy were permeable accepting and integrating non-local individuals, as well as importing a wide range of raw materials, commodities, and ideas from networks spanning continental Europe and the Mediterranean. During the second millennium BC, the communities of Northern Italy engaged in a progressive stabilization of settlements, culminating in the large polities of the end of the Middle/beginning of the Late Bronze Age pivoted around large defended centres (the Terramare). Although a wide range of exotic archaeological materials indicates that the inhabitants of the Po plain increasingly took part in the networks of Continental European and the Eastern Mediterranean, we should not overlook the fact that the dynamics of interaction were also extremely active on local and regional levels. Mobility patterns have been explored for three key-sites, spanning the Early to Late Bronze Age (1900â1100 BC), namely SantâEurosia, Casinalbo and Fondo Paviani, through strontium and oxygen isotope analysis on a large sample size (more than 100 individuals). The results, integrated with osteological and archaeological data, document for the first time in this area that movements of people occurred mostly within a territorial radius of 50 km, but also that larger nodes in the settlement system (such as Fondo Paviani) included individuals from more distant areas. This suggests that, from a demographic perspective, the process towards a more complex socio-political system in Bronze Age Northern Italy was triggered by a largely, but not completely, internal process, stemming from the dynamics of intra-polity networks and local/regional power relationships
World citation and collaboration networks: uncovering the role of geography in science
Modern information and communication technologies, especially the Internet,
have diminished the role of spatial distances and territorial boundaries on the
access and transmissibility of information. This has enabled scientists for
closer collaboration and internationalization. Nevertheless, geography remains
an important factor affecting the dynamics of science. Here we present a
systematic analysis of citation and collaboration networks between cities and
countries, by assigning papers to the geographic locations of their authors'
affiliations. The citation flows as well as the collaboration strengths between
cities decrease with the distance between them and follow gravity laws. In
addition, the total research impact of a country grows linearly with the amount
of national funding for research & development. However, the average impact
reveals a peculiar threshold effect: the scientific output of a country may
reach an impact larger than the world average only if the country invests more
than about 100,000 USD per researcher annually.Comment: Published version. 9 pages, 5 figures + Appendix, The world citation
and collaboration networks at both city and country level are available at
http://becs.aalto.fi/~rajkp/datasets.htm
Learning to Infer Social Ties in Large Networks
Abstract. In online social networks, most relationships are lack of meaning labels (e.g., âcolleague â and âintimate friendsâ), simply because users do not take the time to label them. An interesting question is: can we automatically infer the type of social relationships in a large network? what are the fundamental factors that imply the type of social relation-ships? In this work, we formalize the problem of social relationship learn-ing into a semi-supervised framework, and propose a Partially-labeled Pairwise Factor Graph Model (PLP-FGM) for learning to infer the type of social ties. We tested the model on three different genres of data sets: Publication, Email and Mobile. Experimental results demonstrate that the proposed PLP-FGM model can accurately infer 92.7 % of advisor-advisee relationships from the coauthor network (Publication), 88.0 % of manager-subordinate relationships from the email network (Email), and 83.1 % of the friendships from the mobile network (Mobile). Finally, we develop a distributed learning algorithm to scale up the model to real large networks.
Relationships between CYP2D6 phenotype, breast cancer and hot flushes in women at high risk of breast cancer receiving prophylactic tamoxifen: results from the IBIS-I trial
Licensed under a Creative Commons Attribution Non-Commercial Share Alike Licens
Computational fact checking from knowledge networks
Traditional fact checking by expert journalists cannot keep up with the
enormous volume of information that is now generated online. Computational fact
checking may significantly enhance our ability to evaluate the veracity of
dubious information. Here we show that the complexities of human fact checking
can be approximated quite well by finding the shortest path between concept
nodes under properly defined semantic proximity metrics on knowledge graphs.
Framed as a network problem this approach is feasible with efficient
computational techniques. We evaluate this approach by examining tens of
thousands of claims related to history, entertainment, geography, and
biographical information using a public knowledge graph extracted from
Wikipedia. Statements independently known to be true consistently receive
higher support via our method than do false ones. These findings represent a
significant step toward scalable computational fact-checking methods that may
one day mitigate the spread of harmful misinformation
Theories for influencer identification in complex networks
In social and biological systems, the structural heterogeneity of interaction
networks gives rise to the emergence of a small set of influential nodes, or
influencers, in a series of dynamical processes. Although much smaller than the
entire network, these influencers were observed to be able to shape the
collective dynamics of large populations in different contexts. As such, the
successful identification of influencers should have profound implications in
various real-world spreading dynamics such as viral marketing, epidemic
outbreaks and cascading failure. In this chapter, we first summarize the
centrality-based approach in finding single influencers in complex networks,
and then discuss the more complicated problem of locating multiple influencers
from a collective point of view. Progress rooted in collective influence
theory, belief-propagation and computer science will be presented. Finally, we
present some applications of influencer identification in diverse real-world
systems, including online social platforms, scientific publication, brain
networks and socioeconomic systems.Comment: 24 pages, 6 figure
Geographic constraints on social network groups
Social groups are fundamental building blocks of human societies. While our
social interactions have always been constrained by geography, it has been
impossible, due to practical difficulties, to evaluate the nature of this
restriction on social group structure. We construct a social network of
individuals whose most frequent geographical locations are also known. We also
classify the individuals into groups according to a community detection
algorithm. We study the variation of geographical span for social groups of
varying sizes, and explore the relationship between topological positions and
geographic positions of their members. We find that small social groups are
geographically very tight, but become much more clumped when the group size
exceeds about 30 members. Also, we find no correlation between the topological
positions and geographic positions of individuals within network communities.
These results suggest that spreading processes face distinct structural and
spatial constraints.Comment: 10 pages, 5 figure
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