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 $\textit{ab-initio}$ 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 $\textit{ab-initio}$ 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