3,688,194 research outputs found
A complex network perspective on clinical science
Contemporary classification systems for mental disorders assume that abnormal behaviors are expressions of latent disease entities. An alternative to the latent disease model is the complex network approach. Instead of assuming that symptoms arise from an underlying disease entity, the complex network approach holds that disorders exist as systems of interrelated elements of a network. This approach also provides a framework for the understanding of therapeutic change. Depending on the structure of the network, change can occur abruptly once the network reaches a critical threshold (the tipping point). Homogeneous and highly connected networks often recover more slowly from local perturbations when the network approaches the tipping point, potentially making it possible to predict treatment change, relapse, and recovery. In this article, we discuss the complex network approach as an alternative to the latent disease model and its implications for classification, therapy, relapse, and recovery.R34 MH086668 - NIMH NIH HHS; R01 AT007257 - NCCIH NIH HHS; R21 MH101567 - NIMH NIH HHS; R34 MH099311 - NIMH NIH HHS; R21 MH102646 - NIMH NIH HHS; K23 MH100259 - NIMH NIH HHS; R01 MH099021 - NIMH NIH HH
Wildlife tourism, science and actor network theory
Wildlife tourism is an important component of tourism worldwide. However, for many species little is known about the possible impacts from tourist-wildlife interactions. Previous research has identified barriers to such science being undertaken but this science-wildlife tourism interface remains poorly understood. Actor-network theory, with its attention to the actors and relationships that make science possible, was used to describe and analyze the development and decline of scientific research into the effects of tourism on wildlife in the Antarctic region. This study concludes that actor-network theory provides a robust description of the complex role and positioning of science in wildlife tourism, while at the same time suggesting that further attention to actors' relative power and scientists' normative beliefs are essential elements of analysis
Improving VANET Protocols via Network Science
Developing routing protocols for Vehicular Ad Hoc Networks (VANETs) is a
significant challenge in these large, self- organized and distributed networks.
We address this challenge by studying VANETs from a network science perspective
to develop solutions that act locally but influence the network performance
globally. More specifically, we look at snapshots from highway and urban VANETs
of different sizes and vehicle densities, and study parameters such as the node
degree distribution, the clustering coefficient and the average shortest path
length, in order to better understand the networks' structure and compare it to
structures commonly found in large real world networks such as small-world and
scale-free networks. We then show how to use this information to improve
existing VANET protocols. As an illustrative example, it is shown that, by
adding new mechanisms that make use of this information, the overhead of the
urban vehicular broadcasting (UV-CAST) protocol can be reduced substantially
with no significant performance degradation.Comment: Proceedings of the 2012 IEEE Vehicular Networking Conference (VNC),
Korea, November 201
Punishment diminishes the benefits of network reciprocity in social dilemma experiments
Network reciprocity has been widely advertised in theoretical studies as one of the basic cooperation-promoting mechanisms, but experimental evidence favoring this type of reciprocity was published only recently. When organized in an unchanging network of social contacts, human subjects cooperate provided the following strict condition is satisfied: The benefit of cooperation must outweigh the total cost of cooperating with all neighbors. In an attempt to relax this condition, we perform social dilemma experiments wherein network reciprocity is aided with another theoretically hypothesized cooperation-promoting mechanism—costly punishment. The results reveal how networks promote and stabilize cooperation. This stabilizing effect is stronger in a smaller-size neighborhood, as expected from theory and experiments. Contrary to expectations, punishment diminishes the benefits of network reciprocity by lowering assortment, payoff per round, and award for cooperative behavior. This diminishing effect is stronger in a larger-size neighborhood. An immediate implication is that the psychological effects of enduring punishment override the rational response anticipated in quantitative models of cooperation in networks.We thank J. H. Lee for useful discussions. M.J. and Z.W. were, respectively, supported by the Research Grant Program of Inamori Foundation and the Chinese Young 1000 Talents Plan. B.P. received support from the Slovenian Research Agency (ARRS) and the Croatian Science Foundation through Projects J5-8236 and 5349, respectively. S.H. thanks the Israel-Italian collaborative project Network Cyber Security (NECST), Israel Science Foundation, Office of Naval Research (ONR), Japan Science Foundation, and the US-Israel Binational Science Foundation and the US National Science Foundation (BSF-NSF) for financial support. The Boston University Center for Polymer Studies is supported by NSF Grants PHY-1505000, CMMI-1125290, and CHE-1213217, by Defense Threat Reduction Agency (DTRA) Grant HDTRA1-14-1-0017, and by Department of Energy (DOE) Contract DE-AC07-05Id14517. (Inamori Foundation; Chinese Young 1000 Talents Plan; J5-8236 - Slovenian Research Agency (ARRS); 5349 - Croatian Science Foundation; Israel-Italian collaborative project Network Cyber Security (NECST); Israel Science Foundation; Office of Naval Research (ONR); Japan Science Foundation; US-Israel Binational Science Foundation; US National Science Foundation (BSF-NSF); PHY-1505000 - NSF; CMMI-1125290 - NSF; CHE-1213217 - NSF; HDTRA1-14-1-0017 - Defense Threat Reduction Agency (DTRA); DE-AC07-05Id14517 - Department of Energy (DOE))Published versio
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