Angular distribution of photoluminescence as a probe of Bose Condensation of trapped excitons

Recent experiments on two-dimensional exciton systems have shown the excitons collect in shallow in-plane traps. We find that Bose condensation in a trap results in a dramatic change of the exciton photoluminescence (PL) angular distribution. The long-range coherence of the condensed state gives rise to a sharply focussed peak of radiation in the direction normal to the plane. By comparing the PL profile with and without Bose Condensation we provide a simple diagnostic for the existence of a Bose condensate. The PL peak has strong temperature dependence due to the thermal order parameter phase fluctuations across the system. The angular PL distribution can also be used for imaging vortices in the trapped condensate. Vortex phase spatial variation leads to destructive interference of PL radiation in certain directions, creating nodes in the PL distribution that imprint the vortex configuration.Comment: 4 pages, 3 figure

The impact of contact tracing in clustered populations

The tracing of potentially infectious contacts has become an important part of the control strategy for many infectious diseases, from early cases of novel infections to endemic sexually transmitted infections. Here, we make use of mathematical models to consider the case of partner notification for sexually transmitted infection, however these models are sufficiently simple to allow more general conclusions to be drawn. We show that, when contact network structure is considered in addition to contact tracing, standard “mass action” models are generally inadequate. To consider the impact of mutual contacts (specifically clustering) we develop an improvement to existing pairwise network models, which we use to demonstrate that ceteris paribus, clustering improves the efficacy of contact tracing for a large region of parameter space. This result is sometimes reversed, however, for the case of highly effective contact tracing. We also develop stochastic simulations for comparison, using simple re-wiring methods that allow the generation of appropriate comparator networks. In this way we contribute to the general theory of network-based interventions against infectious disease

Stationary waves in a superfluid exciton gas in quantum Hall bilayers

Stationary waves in a superfluid magnetoexciton gas in nu = 1 quantum Hall bilayers are considered. The waves are induced by counter-propagating electrical currents that flow in a system with a point obstacle. It is shown that stationary waves can emerge only in imbalanced bilayers in a certain diapason of currents. It is found that the stationary wave pattern is modified qualitatively under a variation of the ratio of the interlayer distance to the magnetic length d/l. The advantages of use graphene-dielectric-graphene sandwiches for the observation of stationary waves are discussed. We determine the range of parameters (the dielectric constant of the layer that separates two graphene layers and the ratio d/l) for which the state with superfluid magnetoexcitons can be realized in such sandwiches. Typical stationary wave patterns are presented as density plotsComment: 17 pages, 8 figure

Dynamics of multi-stage infections on networks

This paper investigates the dynamics of infectious diseases with a nonexponentially distributed infectious period. This is achieved by considering a multistage infection model on networks. Using pairwise approximation with a standard closure, a number of important characteristics of disease dynamics are derived analytically, including the final size of an epidemic and a threshold for epidemic outbreaks, and it is shown how these quantities depend on disease characteristics, as well as the number of disease stages. Stochastic simulations of dynamics on networks are performed and compared to output of pairwise models for several realistic examples of infectious diseases to illustrate the role played by the number of stages in the disease dynamics. These results show that a higher number of disease stages results in faster epidemic outbreaks with a higher peak prevalence and a larger final size of the epidemic. The agreement between the pairwise and simulation models is excellent in the cases we consider

Insights from quantitative and mathematical modelling on the proposed 2030 goal for gambiense human African trypanosomiasis (gHAT)

Gambiense human African trypanosomiasis (gHAT) is a parasitic, vector-borne neglected tropical disease that has historically affected populations across West and Central Africa and can result in death if untreated. Following from the success of recent intervention programmes against gHAT, the World Health Organization (WHO) has defined a 2030 goal of global elimination of transmission (EOT). The key proposed indicator to measure achievement of the goal is to have zero reported cases. Results of previous mathematical modelling and quantitative analyses are brought together to explore both the implications of the proposed indicator and the feasibility of achieving the WHO goal. Whilst the indicator of zero case reporting is clear and measurable, it is an imperfect proxy for EOT and could arise either before or after EOT is achieved. Lagging reporting of infection and imperfect diagnostic specificity could result in case reporting after EOT, whereas the converse could be true due to underreporting, lack of coverage, and cryptic human and animal reservoirs. At the village-scale, the WHO recommendation of continuing active screening until there are three years of zero cases yields a high probability of local EOT, but extrapolating this result to larger spatial scales is complex. Predictive modelling of gHAT has consistently found that EOT by 2030 is unlikely across key endemic regions if current medical-only strategies are not bolstered by improved coverage, reduced time to detection and/or complementary vector control. Unfortunately, projected costs for strategies expected to meet EOT are high in the short term and strategies that are cost-effective in reducing burden are unlikely to result in EOT by 2030. Future modelling work should aim to provide predictions while taking into account uncertainties in stochastic dynamics and infection reservoirs, as well as assessment of multiple spatial scales, reactive strategies, and measurable proxies of EOT

Functional significance may underlie the taxonomic utility of single amino acid substitutions in conserved proteins

We hypothesized that some amino acid substitutions in conserved proteins that are strongly fixed by critical functional roles would show lineage-specific distributions. As an example of an archetypal conserved eukaryotic protein we considered the active site of ß-tubulin. Our analysis identified one amino acid substitution—ß-tubulin F224—which was highly lineage specific. Investigation of ß-tubulin for other phylogenetically restricted amino acids identified several with apparent specificity for well-defined phylogenetic groups. Intriguingly, none showed specificity for “supergroups” other than the unikonts. To understand why, we analysed the ß-tubulin Neighbor-Net and demonstrated a fundamental division between core ß-tubulins (plant-like) and divergent ß-tubulins (animal and fungal). F224 was almost completely restricted to the core ß-tubulins, while divergent ß-tubulins possessed Y224. Thus, our specific example offers insight into the restrictions associated with the co-evolution of ß-tubulin during the radiation of eukaryotes, underlining a fundamental dichotomy between F-type, core ß-tubulins and Y-type, divergent ß-tubulins. More broadly our study provides proof of principle for the taxonomic utility of critical amino acids in the active sites of conserved proteins

ENSO and the Carbon Cycle

This is the author accepted manuscript. The final version is available from the American Geophysical Union via the DOI in this recordObservational studies of atmospheric CO2, land ecosystems, and ocean processes show that variability in the carbon cycle is closely related with ENSO. Years with a warm anomaly in the tropical Pacific show a faster CO2 rise due to weaker land carbon sinks, particularly in the tropics, with a partial offset by stronger net uptake by oceans. The opposite happens in years with cool Pacific SST anomalies. This relationship holds for small ENSO SST anomalies as well as large ones and is robust enough for the annual CO2 growth rate anomaly to be highly predictable on the basis of SST observations and forecasts. Generally, variability in the land‐atmosphere carbon flux is mainly driven by physiological processes (photosynthesis and/or respiration), with a smaller contribution from fire. Fire was important in the 1997–1998 El Niño, making a major contribution to the CO2 rise, which can be viewed as anthropogenic in nature since the ignition was caused by humans. However, in the 2015–2016 El Niño event, the change in land carbon flux was mainly due to physiological processes, particularly reduced productivity. In the oceans, El Niño conditions involve decreased upwelling of carbon in the equatorial Pacific due to a weakening of the trade winds, causing this region to become a weaker sink of CO2, or near neutral if the El Niño event is strong. The year‐to‐year variations in the rate of CO2 rise can be successfully reconstructed and predicted on the basis of sea surface temperatures in the Pacific. ENSO‐CO2 relationships may also provide an emergent constraint on the strength of climate‐carbon cycle feedbacks on future anthropogenic climate change

Invasion dynamics of Asian hornet, Vespa velutina (Hymenoptera: Vespidae) : a case study of a commune in south-west France

Asian hornet, Vespa velutina Lepeletier nests were discovered in 2007 in Andernos-les-Bains on the south-west coast of France, 3 years after the first reported sightings in France. The number of nests increased in the commune over the following 7 years, despite local authorities enacting a destruction policy. The nests existed in close proximity to one another leading to a high density of over 10 nests per square kilometre in urban areas. New information on the chosen habitat for nests is presented, and the differences between primary and secondary locations are evident, with primary nests mostly occupying buildings and man-made structures, while secondary nests were found on trees. Using Bayesian inference methods, we fit a basic model to the observational data, which allows us to estimate key demographic parameters. This model fit is highly informative for predicting V. velutina spread and colonisation of other at-risk regions, and suggests that local control has a limited impact on the spread of V. velutina once established within a region