What makes or breaks a campaign to stop an invading plant pathogen?

Diseases in humans, animals and plants remain an important challenge in our society. Effective control of invasive pathogens often requires coordinated concerted action of a large group of stakeholders. Both epidemiological and human behavioural factors influence the outcome of a disease control campaign. In mathematical models that are frequently used to guide such campaigns, human behaviour is often ill-represented, if at all. Existing models of human, animal and plant disease that do incorporate participation or compliance are often driven by pay-offs or direct observations of the disease state. It is however very well known that opinion is an important driving factor of human decision making. Here we consider the case study of Citrus Huanglongbing disease (HLB), which is an acute bacterial disease that threatens the sustainability of citrus production across the world. We show how by coupling an epidemiological model of this invasive disease with an opinion dynamics model we are able to answer the question: What makes or breaks the effectiveness of a disease control campaign? Frequent contact between stakeholders and advisors is shown to increase the probability of successful control. More surprisingly, we show that informing stakeholders about the effectiveness of control methods is of much greater importance than prematurely increasing their perceptions of the risk of infection. We discuss the overarching consequences of this finding and the effect on human as well as plant disease epidemics

Multilayer motif analysis of brain networks

This work was partially supported by the EU-LASAGNE Project, Contract No. 318132 (STREP)

Bioinspired snapping-claw apparatus to study hydrodynamic cavitation effects on the corrosion of metallic samples

A creative low-cost and compact mechanical device that mimics the rapid closure of the pistol shrimp claw was used to conduct electrochemical experiments, in order to study the effects of hydrodynamic cavitation on the corrosion of aluminum and steel samples. Current-time curves show significant changes associated with local variations in dissolved O2 concentration, cavitation-induced erosion and changes in the nature of the surface corrosion products

High-fidelity simulations of CdTe vapor deposition from a new bond-order potential-based molecular dynamics method

CdTe has been a special semiconductor for constructing the lowest-cost solar cells and the CdTe-based Cd1-xZnxTe alloy has been the leading semiconductor for radiation detection applications. The performance currently achieved for the materials, however, is still far below the theoretical expectations. This is because the property-limiting nanoscale defects that are easily formed during the growth of CdTe crystals are difficult to explore in experiments. Here we demonstrate the capability of a bond order potential-based molecular dynamics method for predicting the crystalline growth of CdTe films during vapor deposition simulations. Such a method may begin to enable defects generated during vapor deposition of CdTe crystals to be accurately explored

Variability in commercial demand for tree saplings affects the probability of introducing exotic forest diseases

1. Several devastating forest pathogens are suspected or known to have entered the UK through imported planting material. The nursery industry is a key business of the tree trade network. Variability in demand for trees makes it difficult for nursery owners to predict how many trees to produce in their nursery. When in any given year, the demand for trees is larger than the production, nursery owners buy trees from foreign sources to match market demand. These imports may introduce exotic diseases. 2. We have developed a model of the dynamics of plant production linked to an economic model. We have used this to quantify the effect of demand variability on the risk of introducing an exotic disease. 3. We find that: (a) When the cost of producing a tree in a UK nursery is considerably smaller than the cost of importing a tree (in the example presented, less than half the importing cost), the risk of introducing an exotic disease is hardly affected by an increase in demand variability. (b) When the cost of producing a tree in the nursery is smaller than, but not very different from the cost of importing a tree, the risk of importing exotic diseases increases with increasing demand variability. 4. Synthesis and applications. Our model and results demonstrate how a balanced management of demand variability and costs can reduce the risk of importing an exotic forest disease according to the management strategy adopted. For example, a management strategy that can reduce the demand variability, the ratio of production to import cost or both, optimizes the nursery gross margin when mainly own-produced trees are commercialized. This can also translate into a reduction of the risk of introducing exotic forest diseases due to the small number of imported trees for sale

Ferromagnetic resonance assisted optomechanical magnetometer

The resonant enhancement of mechanical and optical interaction in optomechanical cavities enables their use as extremely sensitive displacement and force detectors. In this work we demonstrate a hybrid magnetometer that exploits the coupling between the resonant excitation of spin waves in a ferromagnetic insulator and the resonant excitation of the breathing mechanical modes of a glass microsphere deposited on top. The interaction is mediated by magnetostriction in the ferromagnetic material and the consequent mechanical driving of the microsphere. The magnetometer response thus relies on the spectral overlap between the ferromagnetic resonance and the mechanical modes of the sphere, leading to a peak sensitivity better than 900 pT Hz$^{-1/2}$ at 206 MHz when the overlap is maximized. By externally tuning the ferromagnetic resonance frequency with a static magnetic field we demonstrate sensitivity values at resonance around a few nT Hz$^{-1/2}$ up to the GHz range. Our results show that our hybrid system can be used to build high-speed sensor of oscillating magnetic fields

Properties of iron-modified-by-silver supported on mordenite as catalysts for nox reduction

A series of mono and bimetallic catalysts based on a Fe-Ag mixture deposited on mordenite was prepared by ion-exchange and evaluated in the catalytic activity test of the de-NOx reaction in the presence of CO/C3H6. The activity results showed that the most active samples were the Fe-containing ones, and at high temperatures, a co-promoter effect of Ag on the activity of Fe catalysts was also observed. The influence of the order of cation deposition on catalysts formation and their physicochemical properties was studied by FTIR (Fourier Transform Infrared Spectroscopy) of adsorbed NO, XANES (X-ray Absorption Near-Edge Structure), and EXAFS (Extended X-ray Absorption Fine Structure) and discussed in terms of the state of iron. Results of Fe K-edge XANES oscillations showed that, in FeMOR catalysts, iron was present in a disordered state as Fe3+ and Fe2+. In FeAgMOR, the prevailing species was Fe3+, while in the AgFeMOR catalyst, the state of iron was intermediate or mixed between FeMOR and FeAgMOR. The Fe K-edge EXAFS results were characteristic of a disordered phase, the first coordination sphere being asymmetric with two different Fe-O distances. In FeAgMOR and AgFeMOR, coordination of Fe-O was similar to Fe2O3 with a few amount of Fe2+ species. We may conclude that, in the bimetallic FeAgMOR and AgFeMOR samples, a certain amount of tetrahedral Al3+ ions in the mordenite framework is replaced by Fe3+ ions, confirming the previous reports that these species are active sites for the de-NOx reaction. Based on the thermodynamic analysis and experimental data, also, it was confirmed that the order of deposition of the components influenced the mechanism of active sites’ formation during the two steps ion-exchange synthesis

An efficient semiparametric maxima estimator of the extremal index

The extremal index $\theta$, a measure of the degree of local dependence in the extremes of a stationary process, plays an important role in extreme value analyses. We estimate $\theta$ semiparametrically, using the relationship between the distribution of block maxima and the marginal distribution of a process to define a semiparametric model. We show that these semiparametric estimators are simpler and substantially more efficient than their parametric counterparts. We seek to improve efficiency further using maxima over sliding blocks. A simulation study shows that the semiparametric estimators are competitive with the leading estimators. An application to sea-surge heights combines inferences about $\theta$ with a standard extreme value analysis of block maxima to estimate marginal quantiles.Comment: 17 pages, 7 figures. Minor edits made to version 1 prior to journal publication. The final publication is available at Springer via http://dx.doi.org/10.1007/s10687-015-0221-