214 research outputs found
Contain or eradicate? Optimizing the management goal for Australian acacia invasions in the face of uncertainty
Aim To identify whether eradication or containment is expected to be the most cost-effective management goal for an isolated invasive population when knowledge about the current extent is uncertain.
Location Global and South Africa.
Methods We developed a decision analysis framework to analyse the best management goal for an invasive species population (eradication, containment or take no action) when knowledge about the current extent is uncertain. We used value of information analysis to identify when investment in learning about the extent will improve this decision-making and tested the sensitivity of the conclusions to different parameters (e.g. spread rate, maximum extent, and
management efficacy and cost). The model was applied to Acacia paradoxa DC, an Australian shrub with an estimated invasive extent of 310 ha on Table Mountain, South Africa.
Results Under the parameters used, attempting eradication is cost-effective for
infestations of up to 777 ha. However, if the invasion extent is poorly known, then attempting eradication is only cost-effective for infestations estimated as
296 ha or smaller. The value of learning is greatest (maximum of 8% saving) when infestation extent is poorly known and if it is close to the maximum extent for which attempting eradication is optimal. The optimal management action is most sensitive to the probability that the action succeeds (which depends on the extent), with the discount rate and cost of management also important, but spread rate less so. Over a 20-year time-horizon, attempting to eradicate
A. paradoxa from South Africa is predicted to cost on average ZAR 8 million if the extent is known, and if our current estimate is poor, ZAR 33.6 million as opposed to ZAR 32.8 million for attempting containment.
Main conclusions Our framework evaluates the cost-effectiveness of attempting eradication or containment of an invasive population that takes uncertainty in population extent into account. We show that incorporating uncertainty in the analysis avoids overly optimistic beliefs about the effectiveness of management enabling better management decisions. For A. paradoxa in South Africa,
attempting to eradicate is likely to be cost-effective, particularly if resources are
allocated to better understand and improve management efficacy.Centre of Excellence for Invasion Biolog
Variational Monte Carlo study of the ground state properties and vacancy formation energy of solid para-H2 using a shadow wave function
A Shadow Wave Function (SWF) is employed along with Variational Monte Carlo
techniques to describe the ground state properties of solid molecular
para-hydrogen. The study has been extended to densities below the equilibrium
value, to obtain a parameterization of the SWF useful for the description of
inhomogeneous phases. We also present an estimate of the vacancy formation
energy as a function of the density, and discuss the importance of relaxation
effects near the vacant site
Approximative treatment of 5f-systems with partial localization due to intra-atomic correlations
Increasing experimental and theoretical evidence points towards a dual nature
of the 5 electrons in actinide-based strongly correlated metallic compounds,
with some 5 electrons being localized and others delocalized. In a recent
paper (PRB xxx, 2004), we suggested the interplay of intra-atomic correlations
as described by Hund's rules and a weakly anisotropic hopping (hybridization)
as a possible mechanism. The purpose of the present work is to provide a first
step towards a microscopic description of partial localization in solids by
analyzing how well various approximation schemes perform when applied to small
clusters. It is found that many aspects of partial localization are described
appropriately both by a variational wavefunction of Gutzwiller type and by a
treatment which keeps only those interactions which are present in LDA+U
calculations. In contrast, the energies and phase diagram calculated within the
Hartree Fock approximation show little resemblence with the exact results.
Enhancement of hopping anisotropy by Hund's rule correlations are found in all
approximations.Comment: 9 pages, 9 figure
Disordered Boson Systems: A Perturbative Study
A hard-core disordered boson system is mapped onto a quantum spin 1/2
XY-model with transverse random fields. It is then generalized to a system of
spins with an arbitrary magnitude S and studied through a 1/S expansion. The
first order 1/S expansion corresponds to a spin-wave theory. The effect of weak
disorder is studied perturbatively within such a first order 1/S scheme. We
compute the reduction of the speed of sound and the life time of the Bloch
phonons in the regime of weak disorder. Generalizations of the present study to
the strong disordered regime are discussed.Comment: 27 pages, revte
Critical Currents and Vortex States at Fractional Matching Fields in Superconductors with Periodic Pinning
We study vortex states and dynamics in 2D superconductors with periodic
pinning at fractional sub-matching fields using numerical simulations. For
square pinning arrays we show that ordered states form at 1/1, 1/2, and 1/4
filling fractions while only partially ordered states form at other filling
fractions, such as 1/3 and 1/5, in agreement with recent imaging experiments.
For triangular pinning arrays we observe matching effects at filling fractions
of 1/1, 6/7, 2/3, 1/3, 1/4, 1/6, and 1/7. For both square and triangular
pinning arrays we also find that, for certian sub-matching fillings, vortex
configurations depend on pinning strength. For weak pinning, ordering in which
a portion of the vortices are positioned between pinning sites can occur.
Depinning of the vortices at the matching fields, where the vortices are
ordered, is elastic while at the incommensurate fields the motion is plastic.
At the incommensurate fields, as the applied driving force is increased, there
can be a transition to elastic flow where the vortices move along the pinning
sites in 1D channels and a reordering transition to a triangular or distorted
triangular lattice. We also discuss the current-voltage curves and how they
relate to the vortex ordering at commensurate and incommensurate fields.Comment: 14 figure
Nature of the quantum phase transitions in the two-dimensional hardcore boson model
We use two Quantum Monte Carlo algorithms to map out the phase diagram of the
two-dimensional hardcore boson Hubbard model with near () and next near
() neighbor repulsion. At half filling we find three phases: Superfluid
(SF), checkerboard solid and striped solid depending on the relative values of
, and the kinetic energy. Doping away from half filling, the
checkerboard solid undergoes phase separation: The superfluid and solid phases
co-exist but not as a single thermodynamic phase. As a function of doping, the
transition from the checkerboard solid is therefore first order. In contrast,
doping the striped solid away from half filling instead produces a striped
supersolid phase: Co-existence of density order with superfluidity as a single
phase. One surprising result is that the entire line of transitions between the
SF and checkerboard solid phases at half filling appears to exhibit dynamical
O(3) symmetry restoration. The transitions appear to be in the same
universality class as the special Heisenberg point even though this symmetry is
explicitly broken by the interaction.Comment: 10 pages, 14 eps figures, include
Context-dependent representation of within- and between-model uncertainty: Aggregating probabilistic predictions in infectious disease epidemiology
Probabilistic predictions support public health planning and decision making, especially in infectious disease emergencies. Aggregating outputs from multiple models yields more robust predictions of outcomes and associated uncertainty. While the selection of an aggregation method can be guided by retrospective performance evaluations, this is not always possible. For example, if predictions are conditional on assumptions about how the future will unfold (e.g. possible interventions), these assumptions may never materialize, precluding any direct comparison between predictions and observations. Here, we summarize literature on aggregating probabilistic predictions, illustrate various methods for infectious disease predictions via simulation, and present a strategy for choosing an aggregation method when empirical validation cannot be used. We focus on the linear opinion pool (LOP) and Vincent average, common methods that make different assumptions about between-prediction uncertainty. We contend that assumptions of the aggregation method should align with a hypothesis about how uncertainty is expressed within and between predictions from different sources. The LOP assumes that between-prediction uncertainty is meaningful and should be retained, while the Vincent average assumes that between-prediction uncertainty is akin to sampling error and should not be preserved. We provide an R package for implementation. Given the rising importance of multi-model infectious disease hubs, our work provides useful guidance on aggregation and a deeper understanding of the benefits and risks of different approaches
Stable Coexistence of an Invasive Plant and Biocontrol Agent: A Parameterized Coupled Plant-Herbivore Model
1. Coupled plant-herbivore models, allowing feedback from plant to herbivore populations and vice versa, enable us to predict the impact of biocontrol agents on their target weed populations; however, they are rarely used in biocontrol studies. We describe the population biology of the invasive plant Echium plantagineum and the weevil Mogulones larvatus, a biocontrol agent, in Australia. In order to understand the dynamics of this plant-herbivore system, a series of coupled models of increasing complexity was developed. 2. A simple model was extended to include a seed bank, density-dependent plant fecundity, competition between weevil larvae and plant tolerance of herbivory, where below a threshold plants could compensate for larval feeding. Parameters and functional forms were estimated from experimental and field data. 3. The plant model, in the absence of the weevil, exhibited stable dynamics and provided a good quantitative description of field densities before the weevil was introduced. 4. In the coupled plant-herbivore model, density dependence in both plant fecundity and weevil larval competition stabilized the dynamics. Without larval competition the model was unstable, and plant tolerance of herbivory exacerbated this instability. This was a result of a time delay in plant response to herbivore densities. 5. Synthesis and applications. The coupled plant-herbivore model allowed us to predict whether stable coexistence of target plant and biocontrol agents was achievable at an acceptable level. We found this to be the case for the Echium-Mogulones system and believe that similar models would be of use when assessing new agents in this and other invasive plant biocontrol systems. Density dependence in new biocontrol agents should be assessed in order to determine whether it is likely to result in the aims of classical biocontrol: low, stable and sustainable populations of plant and herbivore. Further work should be done to characterize the strength of density dependence according to the niche occupied by the biocontrol agent, for example the strength and functional form of density dependence in stem borers may be quite different to that of defoliators
Collaborative Hubs: Making the Most of Predictive Epidemic Modeling
The COVID-19 pandemic has made it clear that epidemic models play an important role in how governments and the public respond to infectious disease crises. Early in the pandemic, models were used to estimate the true number of infections. Later, they estimated key parameters, generated short-term forecasts of outbreak trends, and quantified possible effects of interventions on the unfolding epidemic. In contrast to the coordinating role played by major national or international agencies in weather-related emergencies, pandemic modeling efforts were initially scattered across many research institutions. Differences in modeling approaches led to contrasting results, contributing to confusion in public perception of the pandemic. Efforts to coordinate modeling efforts in so-called âhubsâ have provided governments, healthcare agencies, and the public with assessments and forecasts that reflect the consensus in the modeling community. This has been achieved by openly synthesizing uncertainties across different modeling approaches and facilitating comparisons between them
Measurement of the polarisation of W bosons produced with large transverse momentum in pp collisions at sqrt(s) = 7 TeV with the ATLAS experiment
This paper describes an analysis of the angular distribution of W->enu and
W->munu decays, using data from pp collisions at sqrt(s) = 7 TeV recorded with
the ATLAS detector at the LHC in 2010, corresponding to an integrated
luminosity of about 35 pb^-1. Using the decay lepton transverse momentum and
the missing transverse energy, the W decay angular distribution projected onto
the transverse plane is obtained and analysed in terms of helicity fractions
f0, fL and fR over two ranges of W transverse momentum (ptw): 35 < ptw < 50 GeV
and ptw > 50 GeV. Good agreement is found with theoretical predictions. For ptw
> 50 GeV, the values of f0 and fL-fR, averaged over charge and lepton flavour,
are measured to be : f0 = 0.127 +/- 0.030 +/- 0.108 and fL-fR = 0.252 +/- 0.017
+/- 0.030, where the first uncertainties are statistical, and the second
include all systematic effects.Comment: 19 pages plus author list (34 pages total), 9 figures, 11 tables,
revised author list, matches European Journal of Physics C versio
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