387 research outputs found
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
Reentrant phase behaviour for systems with competition between phase separation and self-assembly
In patchy particle systems where there is competition between the
self-assembly of finite clusters and liquid-vapour phase separation, reentrant
phase behaviour is observed, with the system passing from a monomeric vapour
phase to a region of liquid-vapour phase coexistence and then to a vapour phase
of clusters as the temperature is decreased at constant density. Here, we
present a classical statistical mechanical approach to the determination of the
complete phase diagram of such a system. We model the system as a van der Waals
fluid, but one where the monomers can assemble into monodisperse clusters that
have no attractive interactions with any of the other species. The resulting
phase diagrams show a clear region of reentrance. However, for the most
physically reasonable parameter values of the model, this behaviour is
restricted to a certain range of density, with phase separation still
persisting at high densities.Comment: 13 pages, 10 figure
Surface roughness and thermal conductivity of semiconductor nanowires: going below the Casimir limit
By explicitly considering surface roughness at the atomic level, we
quantitatively show that the thermal conductivity of Si nanowires can be lower
than Casimir's classical limit. However, this violation only occurs for deep
surface degradation. For shallow surface roughness, the Casimir formula is
shown to yield a good approximation to the phonon mean free paths and
conductivity, even for nanowire diameters as thin as 2.22 nm. Our exact
treatment of roughness scattering is in stark contrast with a previously
proposed perturbative approach, which is found to overpredict scattering rates
by an order of magnitude. The obtained results suggest that a complete
theoretical understanding of some previously published experimental results is
still lacking.Comment: 11 pages, 4 figure
Automated computation of materials properties
Materials informatics offers a promising pathway towards rational materials
design, replacing the current trial-and-error approach and accelerating the
development of new functional materials. Through the use of sophisticated data
analysis techniques, underlying property trends can be identified, facilitating
the formulation of new design rules. Such methods require large sets of
consistently generated, programmatically accessible materials data.
Computational materials design frameworks using standardized parameter sets are
the ideal tools for producing such data. This work reviews the state-of-the-art
in computational materials design, with a focus on these automated
frameworks. Features such as structural prototyping and
automated error correction that enable rapid generation of large datasets are
discussed, and the way in which integrated workflows can simplify the
calculation of complex properties, such as thermal conductivity and mechanical
stability, is demonstrated. The organization of large datasets composed of
calculations, and the tools that render them
programmatically accessible for use in statistical learning applications, are
also described. Finally, recent advances in leveraging existing data to predict
novel functional materials, such as entropy stabilized ceramics, bulk metallic
glasses, thermoelectrics, superalloys, and magnets, are surveyed.Comment: 25 pages, 7 figures, chapter in a boo
Large scale risk-assessment of wind-farms on population viability of a globally endangered long-lived raptor
Wind-farms receive public and governmental support as an alternative energy source mitigating air pollution. However, they can have adverse effects on wildlife, particularly through collision with turbines. Research on wind-farm effects has focused on estimating mortality rates, behavioural changes or interspecific differences in vulnerability. Studies dealing with their effects on endangered or rare species populations are notably scarce. We tested the hypothesis that wind-farms increase extinction probability of long-lived species through increments in mortality rates. For this purpose, we evaluate potential consequences of wind-farms on the population dynamics of a globally endangered long-lived raptor in an area where the species maintains its greatest stronghold and wind-farms are rapidly increasing. Nearly one-third of all breeding territories of our model species are in wind-farm risk zones. Our intensive survey shows that wind-farms decrease survival rates of this species differently depending on individual breeding status. Consistent with population monitoring, population projections showed that all subpopulations and the meta-population are decreasing. However, population sizes and, therefore, time to extinction significantly decreased when wind-farm mortality was included in models. Our results represent a qualitative warning exercise showing how very low reductions in survival of territorial and non-territorial birds associated with wind-farms can strongly impact population viability of long-lived species. This highlights the need for examining long-term impacts of wind-farms rather than focusing on short-term mortality, as is often promoted by power companies and some wildlife agencies. Unlike other non-natural causes of mortality difficult to eradicate or control, wind-farm fatalities can be lowered by powering down or removing risky turbines and/or farms, and by placing them outside areas critical for endangered birds. © 2009 Elsevier Ltd. All rights reserved.Peer Reviewe
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