Absence of confinement in (SrTiO3)/(SrTi0:8Nb0:2O3) superlattices

The reduction of dimensionality is an efficient pathway to boost the performances of thermoelectric materials, it leads to the quantum confinement of the carriers and thus to large Seebeck coefficients (S) and it also suppresses the thermal conductivity by increasing the phonon scattering processes. However, quantum confinement in superlattices is not always easy to achieve and needs to be carefully validated. In the past decade, large values of S have been measured in (SrTiO3)/(SrTi0:8Nb0:2O3) superlattices (Nat. Mater. 6, 129 (2007) and Appl. Phys. Lett. 91, 192105 (2007)). In the $\delta$-doped compound, the measured S was almost 6 times larger than that of the bulk material. This huge increase has been attributed to the two dimensional confinement of the carriers in the doped regions. In this work, we demonstrate that the experimental data can be well explained quantitatively within the scenario in which electrons are delocalized in both in-plane and growth directions, hence strongly suggesting that the confinement picture in these superlattices may be unlikely.Comment: 5 figures, manuscript submitte

A Bayesian inference framework to reconstruct transmission trees using epidemiological and genetic data

The accurate identification of the route of transmission taken by an infectious agent through a host population is critical to understanding its epidemiology and informing measures for its control. However, reconstruction of transmission routes during an epidemic is often an underdetermined problem: data about the location and timings of infections can be incomplete, inaccurate, and compatible with a large number of different transmission scenarios. For fast-evolving pathogens like RNA viruses, inference can be strengthened by using genetic data, nowadays easily and affordably generated. However, significant statistical challenges remain to be overcome in the full integration of these different data types if transmission trees are to be reliably estimated. We present here a framework leading to a bayesian inference scheme that combines genetic and epidemiological data, able to reconstruct most likely transmission patterns and infection dates. After testing our approach with simulated data, we apply the method to two UK epidemics of Foot-and-Mouth Disease Virus (FMDV): the 2007 outbreak, and a subset of the large 2001 epidemic. In the first case, we are able to confirm the role of a specific premise as the link between the two phases of the epidemics, while transmissions more densely clustered in space and time remain harder to resolve. When we consider data collected from the 2001 epidemic during a time of national emergency, our inference scheme robustly infers transmission chains, and uncovers the presence of undetected premises, thus providing a useful tool for epidemiological studies in real time. The generation of genetic data is becoming routine in epidemiological investigations, but the development of analytical tools maximizing the value of these data remains a priority. Our method, while applied here in the context of FMDV, is general and with slight modification can be used in any situation where both spatiotemporal and genetic data are available

Estimating sharka dispersal function by stochastic spatiotemporal modelling

Plant viral diseases, and especially the ones transmitted by aerial vectors, can cause considerable yield losses. A good knowledge of the distances of spread is key to the understanding of disease dynamics. Exploratory approaches aiming at characterizing the spatiotemporal distribution of diseased plants are often used to get an insight into the distances of spread. A more powerful approach is based on stochastic spatiotemporal modelling in order to estimate the dispersal function of the disease (probability density function describing the probability for an infectious plant to infect a healthy plant at distance d). In this study, we implemented a method for estimating the dispersal function of the sharka disease. Sharka is one of the most serious diseases of stone fruit trees (Prunus sp.). It is caused by Plum pox virus (PPV, genus Potyvirus), transmitted by at least twenty different aphid species in a non persistent manner. Due to the inefficiency of insecticides and the very rare sources of resistance against the virus available in the host species, prophylactic disease control is based on the removal of the diseased trees in the orchards. Thus, a very good knowledge of the dispersal function of sharka is crucial for building epidemiological models and optimizing the strategies of surveillance and control. We adapted the methodology published by Gibson (1997) based on a Markov chain Monte Carlo (MCMC) algorithm in order to estimate sharka dispersal function from the maps of 157 contiguous peach orchards reporting the exact location and the sanitary status (asymptomatic/symptomatic) of each of the trees during six consecutive years. An estimation method based on the Gibbs sampling algorithm was developed taking into account the specificities of the dataset (more than two dates of observation, annual removal of diseased trees). This estimation algorithm was validated on simulated data and was proved to be more powerful and better adapted to large datasets than the one proposed by Gibson. Moreover, the influence of latency on the estimation of the dispersal function was quantified. This methodology was then used to estimate the dispersal function of the disease from a subset of the real dataset. The methods developed in this study are generic enough to be used and adapted for the estimation of dispersal functions of any disease transmitted in a non persistent manner, and even for diseases with similar characteristics. (Texte intégral

Unified modelling of the thermoelectric properties in SrTiO3

Thermoelectric materials are opening a promising pathway to address energy conversion issues governed by a competition between thermal and electronic transport. Improving the efficiency is a difficult task, a challenge that requires new strategies to unearth optimized compounds. We present a theory of thermoelectric transport in electron doped SrTiO3, based on a realistic tight binding model that includes relevant scattering processes. We compare our calculations against a wide panel of experimental data, both bulk and thin films. We find a qualitative and quantitative agreement over both a wide range of temperatures and carrier concentrations, from light to heavily doped. Moreover, the results appear insensitive to the nature of the dopant La, B, Gd and Nb. Thus, the quantitative success found in the case of SrTiO3, reveals an efficient procedure to explore new routes to improve the thermoelectric properties in oxides.Comment: 5 figures, manuscript submitte

A retrospective analysis of the effects of adopting individual transferable quotas in the Tasmanian red rock lobster,Jasus edwardsii, fishery

Individual transferable quotas (ITQ) were implemented in the Tasmanian red rock lobster fishery in 1998 and ten years later we assessed the impacts on the fishery. Particular attention was devoted to investigating the performances of the fishery with regard to three features identified as major impacts in the literature: rationalization of the fishing fleet, change in fishing strategy in order to maximise the fisher’s profit and concentration of fishing rights and activity. On average, the fishery reacted as expected and reached its objective in terms of reconstruction of the biomass, but the overall assessment in terms of resulting profitability is not very conclusive. There is no evidence of decrease of the profitability over the period of the study but the fishery is more reactive to external factors on its export market in China than to changes in its own structure.The first author is supported by a PhD scholarship co-funded by IFREMER and the joint CSIRO-UTAS Quantitative Marine Science program (QMS

Inferring epidemiological links from deep sequencing data: a statistical learning approach for human, animal and plant diseases

Pathogen sequence data have been exploited to infer who infected whom, by using empirical and model-based approaches. Most of these approaches exploit one pathogen sequence per infected host (e.g. individual, household, field). However, modern sequencing techniques can reveal the polymorphic nature of within-host populations of pathogens. Thus, these techniques provide a subsample of the pathogen variants that were present in the host at the sampling time. Such data are expected to give more insight on epidemiological links than a single sequence per host. In general, a mechanistic viewpoint to transmission and micro-evolution has been followed to infer epidemiological links from these data. Here, we investigate an alternative approach grounded on statistical learning. The idea consists of learning the structure of epidemiological links with a pseudo-evolutionary model applied to training data obtained from contact tracing, for example, and using this initial stage to infer links for the whole dataset. Such an approach has the potential to be particularly valuable in the case of a risk of erroneous mechanistic assumptions, it is sufficiently parsimonious to allow the handling of big datasets in the future, and it is versatile enough to be applied to very different contexts from animal, human and plant epidemiology. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'

Towards Behavioural Models of Fleet Dynamics

Considerable attention has been applied to the development of models explaining how fish stocks change over space and time, from relatively simple stock-recruitment relationships to ecosystem models with a complex food web structure. However, in many case studies fishing effort is assumed to be exogenous and even in dynamic models pre-determined by external factors such as management. An increasing number of operational bio-economic models for the marine environment are including a fleet dynamics component, recognising that fishers respond to changing environmental and economic conditions. These models are based on different assumptions about behaviour. In this review, we examine models of fisher behaviour that are empirically or theoretically developed and tested. In particular, we focus on the range of different economic and social drivers and their relevance to different types of behaviour. We find that economic factors are a dominant driver included in many types of short term behavioural models, although we acknowledge and find that other social factors play a significant role in some types of behaviour. The link between management and economic impacts is reasonably well established, and most bioeconomic models are able to incorporate these feedback systems. Incorporating these other social-dependent behaviours into bioeconomic models, however, is likely to remain a challenge unless links between management and changes in the social drivers are developed.Keywords: Fish and Aquaculture Sectors Development, Fisheries Economics, Fishers Behavio

Cooperation, Norms, and Revolutions: A Unified Game-Theoretical Approach

Cooperation is of utmost importance to society as a whole, but is often challenged by individual self-interests. While game theory has studied this problem extensively, there is little work on interactions within and across groups with different preferences or beliefs. Yet, people from different social or cultural backgrounds often meet and interact. This can yield conflict, since behavior that is considered cooperative by one population might be perceived as non-cooperative from the viewpoint of another. To understand the dynamics and outcome of the competitive interactions within and between groups, we study game-dynamical replicator equations for multiple populations with incompatible interests and different power (be this due to different population sizes, material resources, social capital, or other factors). These equations allow us to address various important questions: For example, can cooperation in the prisoner's dilemma be promoted, when two interacting groups have different preferences? Under what conditions can costly punishment, or other mechanisms, foster the evolution of norms? When does cooperation fail, leading to antagonistic behavior, conflict, or even revolutions? And what incentives are needed to reach peaceful agreements between groups with conflicting interests? Our detailed quantitative analysis reveals a large variety of interesting results, which are relevant for society, law and economics, and have implications for the evolution of language and culture as well

Cryptic trans-lithospheric fault systems at the western margin of South America: implications for the formation and localization of gold-rich deposit superclusters

We present a review of frontier research advances in the investigation of cryptic structures that transect the South American Andes at oblique strike directions. The intersections between these cryptic structures and the superimposed Andean belt correlate with the spatial distribution of gold-rich mineral deposit clusters. The deposit clusters can be described as superclusters, as they comprise various gold deposit types that formed at multiple times throughout the Phanerozoic, impinging repeatedly on the structural intersections. However, the cryptic inherited fault structures are difficult to detect, because their deeper-seated roots are often overlain by younger supracrustal successions, and/or their exposed surface manifestations are structurally obscured by subsequent tectonic-magmatic activity. Thus, it also remains a challenge to constrain the nature and timing of formation, and the respective subsequent evolutionary path, of these proposed pre-Andean structures. Based on various case studies, we demonstrate that the localization of identified Phanerozoic gold deposit superclusters along the western South American margin is fundamentally controlled by structural inheritance often dating back to at least the Mesoproterozoic. Integration of multi-approach observations and datasets allows insights into a larger-scale tectonic history that showcases the successive inheritance of major structures originating from the Amazonian Craton, over the Paleozoic Gondwana margin, into the Cenozoic magmatic belts of the Andes, and even into recent fractures within the subducting oceanic Nazca plate, recording >1.2-billion-years of progressive structural inheritance and growth at one of the longest-lived tectonic margins in Earth history. In contrast to previous models of the spatial distribution of gold deposits, based on statistical approaches and spatial periodicity in self-organized systems focusing on single subduction and/or accretion episodes and belts, we propose that the structural inheritance and intersections are key to the localization of gold deposits in the Andes. In combination with bulk-geochemical data from magmatic rocks, we suggest that inherited structures maintained a trans-lithospheric connectivity to pre-fertilized gold enriched upper mantle reservoirs, which were tapped during multiple tectono-magmatic reactivation episodes