4,264 research outputs found

    Representing the UK's cattle herd as static and dynamic networks

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    Network models are increasingly being used to understand the spread of diseases through sparsely connected populations, with particular interest in the impact of animal movements upon the dynamics of infectious diseases. Detailed data collected by the UK government on the movement of cattle may be represented as a network, where animal holdings are nodes, and an edge is drawn between nodes where a movement of animals has occurred. These network representations may vary from a simple static representation, to a more complex, fully dynamic one where daily movements are explicitly captured. Using stochastic disease simulations, a wide range of network representations of the UK cattle herd are compared. We find that the simpler static network representations are often deficient when compared with a fully dynamic representation, and should therefore be used only with caution in epidemiological modelling. In particular, due to temporal structures within the dynamic network, static networks consistently fail to capture the predicted epidemic behaviour associated with dynamic networks even when parameterized to match early growth rates

    Precise atmospheric oxygen measurements with a paramagnetic oxygen analyzer

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    A methodology has been developed for making continuous, high-precision measurements of atmospheric oxygen concentrations by modifying a commercially available paramagnetic oxygen analyzer. Incorporating several design improvements, an effective precision of 0.2 ppm O-2 from repeated measurements over a 1-hour interval was achieved. This is sufficient to detect background changes in atmospheric O-2 to a level that constrains various aspects of the global carbon cycle. The analyzer was used to measure atmospheric O-2 in a semicontinuous fashion from air sampled from the end of Scripps Pier, La Jolla, California, and data from a 1-week period in August 1996 are shown. The data exhibit strongly anticorrelated changes in O-2 and CO2 caused by local or regional combustion of fossil fuels. During periods of steady background CO2 concentrations, however, we see additional variability in O-2 concentrations, clearly not due to local combustion and presumably due to oceanic sources or sinks of O-2. This variability suggests that in contrast to CO2, higher O-2 sampling rates, such as those provided by continuous measurement programs, may be necessary to define an atmospheric O-2 background and thus aid in validating and interpreting other O-2 data from flask sampling programs. Our results have also demonstrated that this paramagnetic analyzer and gas handling design is well suited for making continuous measurements of atmospheric O-2 and is suitable for placement at remote background air monitoring sites

    Quench dynamics of a disordered array of dissipative coupled cavities

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    We investigate the mean-field dynamics of a system of interacting photons in an array of coupled cavities in presence of dissipation and disorder. We follow the evolution of on an initially prepared Fock state, and show how the interplay between dissipation and disorder affects the coherence properties of the cavity emission and that these properties can be used as signatures of the many-body phase of the whole array.Comment: 8 pages, 10 figures, new reference adde

    Modelling the spread of American foulbrood in honeybees

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    We investigate the spread of American foulbrood (AFB), a disease caused by the bacterium Paenibacillus larvae, that affects bees and can be extremely damaging to beehives. Our dataset comes from an inspection period carried out during an AFB epidemic of honeybee colonies on the island of Jersey during the summer of 2010. The data include the number of hives of honeybees, location and owner of honeybee apiaries across the island. We use a spatial SIR model with an underlying owner network to simulate the epidemic and characterize the epidemic using a Markov chain Monte Carlo (MCMC) scheme to determine model parameters and infection times (including undetected ‘occult’ infections). Likely methods of infection spread can be inferred from the analysis, with both distance- and owner-based transmissions being found to contribute to the spread of AFB. The results of the MCMC are corroborated by simulating the epidemic using a stochastic SIR model, resulting in aggregate levels of infection that are comparable to the data. We use this stochastic SIR model to simulate the impact of different control strategies on controlling the epidemic. It is found that earlier inspections result in smaller epidemics and a higher likelihood of AFB extinction

    Atmospheric potential oxygen: New observations and their implications for some atmospheric and oceanic models

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    Measurements of atmospheric O2/N2 ratios and CO2 concentrations can be combined into a tracer known as atmospheric potential oxygen (APO ≈ O2/N2 + CO2) that is conservative with respect to terrestrial biological activity. Consequently, APO reflects primarily ocean biogeochemistry and atmospheric circulation. Building on the work of Stephens et al. (1998), we present a set of APO observations for the years 1996-2003 with unprecedented spatial coverage. Combining data from the Princeton and Scripps air sampling programs, the data set includes new observations collected from ships in the low-latitude Pacific. The data show a smaller interhemispheric APO gradient than was observed in past studies, and different structure within the hemispheres. These differences appear to be due primarily to real changes in the APO field over time. The data also show a significant maximum in APO near the equator. Following the approach of Gruber et al. (2001), we compare these observations with predictions of APO generated from ocean O2 and CO2 flux fields and forward models of atmospheric transport. Our model predictions differ from those of earlier modeling studies, reflecting primarily the choice of atmospheric transport model (TM3 in this study). The model predictions show generally good agreement with the observations, matching the size of the interhemispheric gradient, the approximate amplitude and extent of the equatorial maximum, and the amplitude and phasing of the seasonal APO cycle at most stations. Room for improvement remains. The agreement in the interhemispheric gradient appears to be coincidental; over the last decade, the true APO gradient has evolved to a value that is consistent with our time-independent model. In addition, the equatorial maximum is somewhat more pronounced in the data than the model. This may be due to overly vigorous model transport, or insufficient spatial resolution in the air-sea fluxes used in our modeling effort. Finally, the seasonal cycles predicted by the model of atmospheric transport show evidence of an excessive seasonal rectifier in the Aleutian Islands and smaller problems elsewhere. Copyright 2006 by the American Geophysical Union

    Fundamentals of Oil and Gas Royalty Calculation

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    Fundamentals of Oil and Gas Royalty Calculation

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    Global surface-ocean pCO2 and sea–air CO2 flux variability from an observation-driven ocean mixed-layer scheme

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    A temporally and spatially resolved estimate of the global surface-ocean CO<sub>2</sub> partial pressure field and the sea–air CO<sub>2</sub> flux is presented, obtained by fitting a simple data-driven diagnostic model of ocean mixed-layer biogeochemistry to surface-ocean CO<sub>2</sub> partial pressure data from the SOCAT v1.5 database. Results include seasonal, interannual, and short-term (daily) variations. In most regions, estimated seasonality is well constrained from the data, and compares well to the widely used monthly climatology by Takahashi et al. (2009). Comparison to independent data tentatively supports the slightly higher seasonal variations in our estimates in some areas. We also fitted the diagnostic model to atmospheric CO<sub>2</sub> data. The results of this are less robust, but in those areas where atmospheric signals are not strongly influenced by land flux variability, their seasonality is nevertheless consistent with the results based on surface-ocean data. From a comparison with an independent seasonal climatology of surface-ocean nutrient concentration, the diagnostic model is shown to capture relevant surface-ocean biogeochemical processes reasonably well. Estimated interannual variations will be presented and discussed in a companion paper
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