6,237 research outputs found
Community structure detection in the evolution of the United States airport network
This is the post-print version of the Article. Copyright © 2013 World Scientific PublishingThis paper investigates community structure in the US Airport Network as it evolved from 1990 to 2010 by looking at six bi-monthly intervals in 1990, 2000 and 2010, using data obtained from the Bureau of Transportation Statistics of the US Department of Transport. The data contained monthly records of origin-destination pairs of domestic airports and the number of passengers carried. The topological properties and the volume of people traveling are both studied in detail, revealing high heterogeneity in space and time. A recently developed community structure detection method, accounting for the spatial nature of these networks, is applied and reveals a picture of the communities within. The patterns of communities plotted for each bi-monthly interval reveal some interesting seasonal variations of passenger flows and airport clusters that do not occupy a single US region. The long-term evolution of the network between those years is explored and found to have consistently improved its stability. The more recent structure of the network (2010) is compared with migration patterns among the four US macro-regions (West, Midwest, Northeast and South) in order to identify possible relationships and the results highlight a clear overlap between US domestic air travel and migration
Intracellular transport driven by cytoskeletal motors: General mechanisms and defects
Cells are strongly out-of-equilibrium systems driven by continuous energy
supply. They carry out many vital functions requiring active transport of
various ingredients and organelles, some being small, others being large. The
cytoskeleton, composed of three types of filaments, determines the shape of the
cell and plays a role in cell motion. It also serves as a road network for the
so-called cytoskeletal motors. These molecules can attach to a cytoskeletal
filament, perform directed motion, possibly carrying along some cargo, and then
detach. It is a central issue to understand how intracellular transport driven
by molecular motors is regulated, in particular because its breakdown is one of
the signatures of some neuronal diseases like the Alzheimer.
We give a survey of the current knowledge on microtubule based intracellular
transport. We first review some biological facts obtained from experiments, and
present some modeling attempts based on cellular automata. We start with
background knowledge on the original and variants of the TASEP (Totally
Asymmetric Simple Exclusion Process), before turning to more application
oriented models. After addressing microtubule based transport in general, with
a focus on in vitro experiments, and on cooperative effects in the
transportation of large cargos by multiple motors, we concentrate on axonal
transport, because of its relevance for neuronal diseases. It is a challenge to
understand how this transport is organized, given that it takes place in a
confined environment and that several types of motors moving in opposite
directions are involved. We review several features that could contribute to
the efficiency of this transport, including the role of motor-motor
interactions and of the dynamics of the underlying microtubule network.
Finally, we discuss some still open questions.Comment: 74 pages, 43 figure
An experimental study of network effects on coordination in asymmetric games
Network structure has often proven to be important in understanding the decision behavior of individuals or agents in different interdependent situations. Computational studies predict that network structure has a crucial influence on behavior in iterated 2 by 2 asymmetric ‘battle of the sexes’ games. We test such behavioral predictions in an experiment with 240 human subjects. We found that as expected the less ‘random’ the network structure, the better the experimental results are predictable by the computational models. In particular, there is an effect of network clustering on the heterogeneity of convergence behavior in the network. We also found that degree centrality and having an even degree are important predictors of the decision behavior of the subjects in the experiment. We thus find empirical validation of predictions made by computational models in a computerized experiment with human subjects
Complex networks analysis in socioeconomic models
This chapter aims at reviewing complex networks models and methods that were
either developed for or applied to socioeconomic issues, and pertinent to the
theme of New Economic Geography. After an introduction to the foundations of
the field of complex networks, the present summary adds insights on the
statistical mechanical approach, and on the most relevant computational aspects
for the treatment of these systems. As the most frequently used model for
interacting agent-based systems, a brief description of the statistical
mechanics of the classical Ising model on regular lattices, together with
recent extensions of the same model on small-world Watts-Strogatz and
scale-free Albert-Barabasi complex networks is included. Other sections of the
chapter are devoted to applications of complex networks to economics, finance,
spreading of innovations, and regional trade and developments. The chapter also
reviews results involving applications of complex networks to other relevant
socioeconomic issues, including results for opinion and citation networks.
Finally, some avenues for future research are introduced before summarizing the
main conclusions of the chapter.Comment: 39 pages, 185 references, (not final version of) a chapter prepared
for Complexity and Geographical Economics - Topics and Tools, P.
Commendatore, S.S. Kayam and I. Kubin Eds. (Springer, to be published
- …