Static and Dynamic Aspects of Scientific Collaboration Networks

Collaboration networks arise when we map the connections between scientists which are formed through joint publications. These networks thus display the social structure of academia, and also allow conclusions about the structure of scientific knowledge. Using the computer science publication database DBLP, we compile relations between authors and publications as graphs and proceed with examining and quantifying collaborative relations with graph-based methods. We review standard properties of the network and rank authors and publications by centrality. Additionally, we detect communities with modularity-based clustering and compare the resulting clusters to a ground-truth based on conferences and thus topical similarity. In a second part, we are the first to combine DBLP network data with data from the Dagstuhl Seminars: We investigate whether seminars of this kind, as social and academic events designed to connect researchers, leave a visible track in the structure of the collaboration network. Our results suggest that such single events are not influential enough to change the network structure significantly. However, the network structure seems to influence a participant's decision to accept or decline an invitation.Comment: ASONAM 2012: IEEE/ACM International Conference on Advances in Social Networks Analysis and Minin

Catchment drainage network scaling laws found experimentally in overland flow morphologies

The scaling relation between the drainage area and stream length (Hack's law), along with exceedance probabilities of drainage area, discharge, and upstream flow network length, is well known for channelized fluvial regions. We report here on a laboratory experiment on an eroding unconsolidated sediment for which no channeling occurred. Laser scanning was used to capture the morphological evolution of the sediment. High-intensity, spatially nonuniform rainfall ensured that the morphology changed substantially over the 16-hr experiment. Based on the surface scans and precipitation distribution, overland flow was estimated with the D8 algorithm, which outputs a flow network that was analyzed statistically. The above-mentioned scaling and exceedance probability relationships for this overland flow network are the same as those found for large-scale catchments and for laboratory experiments with observable channels. In addition, the scaling laws were temporally invariant, even though the network dynamically changed over the course of experiment

Revving up natural killer cells and cytokine-induced killer cells against hematological malignancies

Natural killer (NK) cells belong to innate immunity and exhibit cytolytic activity against infectious pathogens and tumor cells. NK-cell function is finely tuned by receptors that transduce inhibitory or activating signals, such as killer immunoglobulin-like receptors, NK Group 2 member D (NKG2D), NKG2A/CD94, NKp46, and others, and recognize both foreign and self-antigens expressed by NK-susceptible targets. Recent insights into NK-cell developmental intermediates have translated into a more accurate definition of culture conditions for the in vitro generation and propagation of human NK cells. In this respect, interleukin (IL)-15 and IL-21 are instrumental in driving NK-cell differentiation and maturation, and hold great promise for the design of optimal NK-cell culture protocols. Cytokine-induced killer (CIK) cells possess phenotypic and functional hallmarks of both T cells and NK cells. Similar to T cells, they express CD3 and are expandable in culture, while not requiring functional priming for in vivo activity, like NK cells. CIK cells may offer some advantages over other cell therapy products, including ease of in vitro propagation and no need for exogenous administration of IL-2 for in vivo priming. NK cells and CIK cells can be expanded using a variety of clinical-grade approaches, before their infusion into patients with cancer. Herein, we discuss GMP-compliant strategies to isolate and expand human NK and CIK cells for immunotherapy purposes, focusing on clinical trials of adoptive transfer to patients with hematological malignancies

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements