2,340 research outputs found

    Asset-price boom-bust cycles and credit: what is the scope of macro-prudential regulation?

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    Over the recent months, several initiatives have taken place to develop macro-prudential regulation in order to prevent systemic risk and the built-up of financial imbalances. Crucial to the success of such policy is the ability of the macro-prudential authority to identify in due time such imbalances, generally featured by asset-price boom-bust cycles. In this paper, we investigate the possibility of detecting asset-price booms according to alternative identification strategies and assess their robustness. We infer the probability that an asset-price boom turns into an asset-price bust. In addition, we try to disentangle costless or low-cost from costly asset-price booms. We find some evidence that house price booms are more likely to turn into costly recession than stock price booms. Resorting both to a non-parametric approach and a discrete-choice (logit) model, we analyze the ability of a set of indicators to robustly explain costly asset-price booms. According to our results, real long-term interest rates, total investment, real credit and real stock prices tend to increase the probability of a costly housing-price boom, whereas real GDP and house prices tend to increase the probability of a costly stock-price boom. Regarding the latter, credit variables tend to play a less convincing role. From this perspective, we specify the scope of macro-prudential regulation as a set of tools aiming at avoiding "costly" asset-price booms. In doing so, we try both to make the case for state-contingent macro-prudential regulations and to set out clear delineation between monetary and financial stability objectives.Early Warning Indicators , Discrete-Choice Model , Asset Price Booms and Busts , Macro-prudential Regulation , Leaning Against the Wind Policies.

    Continuous Forest Fire Propagation in a Local Small World Network Model

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    This paper presents the development of a new continuous forest fire model implemented as a weighted local small-world network approach. This new approach was designed to simulate fire patterns in real, heterogeneous landscapes. The wildland fire spread is simulated on a square lattice in which each cell represents an area of the land's surface. The interaction between burning and non-burning cells, in the present work induced by flame radiation, may be extended well beyond nearest neighbors. It depends on local conditions of topography and vegetation types. An approach based on a solid flame model is used to predict the radiative heat flux from the flame generated by the burning of each site towards its neighbors. The weighting procedure takes into account the self-degradation of the tree and the ignition processes of a combustible cell through time. The model is tested on a field presenting a range of slopes and with data collected from a real wildfire scenario. The critical behavior of the spreading process is investigated

    Plant clonal morphologies and spatial patterns as self-organized responses to resource-limited environments

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    We propose here to interpret and model peculiar plant morphologies (cushions, tussocks) observed in the Andean altiplano as localized structures. Such structures resulting in a patchy, aperiodic aspect of the vegetation cover are hypothesized to self-organize thanks to the interplay between facilitation and competition processes occurring at the scale of basic plant components biologically referred to as 'ramets'. (Ramets are often of clonal origin.) To verify this interpretation, we applied a simple, fairly generic model (one integro-differential equation) emphasizing via Gaussian kernels non-local facilitative and competitive feedbacks of the vegetation biomass density on its own dynamics. We show that under realistic assumptions and parameter values relating to ramet scale, the model can reproduce some macroscopic features of the observed systems of patches and predict values for the inter-patch distance that match the distances encountered in the reference area (Sajama National Park in Bolivia). Prediction of the model can be confronted in the future to data on vegetation patterns along environmental gradients as to anticipate the possible effect of global change on those vegetation systems experiencing constraining environmental conditions.Comment: 14 pages, 6figure

    Bouncing localized structures in a liquid-crystal light-valve experiment

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    Experimental evidence of bouncing localized structures in a nonlinear optical system is reported.Comment: 4 page

    JPEG steganography with particle swarm optimization accelerated by AVX

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    Digital steganography aims at hiding secret messages in digital data transmitted over insecure channels. The JPEG format is prevalent in digital communication, and images are often used as cover objects in digital steganography. Optimization methods can improve the properties of images with embedded secret but introduce additional computational complexity to their processing. AVX instructions available in modern CPUs are, in this work, used to accelerate data parallel operations that are part of image steganography with advanced optimizations.Web of Science328art. no. e544

    An island based hybrid evolutionary algorithm for optimization

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    This is a post-print version of the article - Copyright @ 2008 Springer-VerlagEvolutionary computation has become an important problem solving methodology among the set of search and optimization techniques. Recently, more and more different evolutionary techniques have been developed, especially hybrid evolutionary algorithms. This paper proposes an island based hybrid evolutionary algorithm (IHEA) for optimization, which is based on Particle swarm optimization (PSO), Fast Evolutionary Programming (FEP), and Estimation of Distribution Algorithm (EDA). Within IHEA, an island model is designed to cooperatively search for the global optima in search space. By combining the strengths of the three component algorithms, IHEA greatly improves the optimization performance of the three basic algorithms. Experimental results demonstrate that IHEA outperforms all the three component algorithms on the test problems.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1

    The XMM-LSS survey: the Class 1 cluster sample over the extended 11 deg2^2 and its spatial distribution

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    This paper presents 52 X-ray bright galaxy clusters selected within the 11 deg2^2 XMM-LSS survey. 51 of them have spectroscopic redshifts (0.05<z<1.060.05<z<1.06), one is identified at zphot=1.9z_{\rm phot}=1.9, and all together make the high-purity "Class 1" (C1) cluster sample of the XMM-LSS, the highest density sample of X-ray selected clusters with a monitored selection function. Their X-ray fluxes, averaged gas temperatures (median TX=2T_X=2 keV), luminosities (median LX,500=5×1043L_{X,500}=5\times10^{43} ergs/s) and total mass estimates (median 5×1013h−1M⊙5\times10^{13} h^{-1} M_{\odot}) are measured, adapting to the specific signal-to-noise regime of XMM-LSS observations. The redshift distribution of clusters shows a deficit of sources when compared to the cosmological expectations, regardless of whether WMAP-9 or Planck-2013 CMB parameters are assumed. This lack of sources is particularly noticeable at 0.4≲z≲0.90.4 \lesssim z \lesssim 0.9. However, after quantifying uncertainties due to small number statistics and sample variance we are not able to put firm (i.e. >3σ>3 \sigma) constraints on the presence of a large void in the cluster distribution. We work out alternative hypotheses and demonstrate that a negative redshift evolution in the normalization of the LX−TXL_{X}-T_X relation (with respect to a self-similar evolution) is a plausible explanation for the observed deficit. We confirm this evolutionary trend by directly studying how C1 clusters populate the LX−TX−zL_{X}-T_X-z space, properly accounting for selection biases. We point out that a systematically evolving, unresolved, central component in clusters and groups (AGN contamination or cool core) can impact the classification as extended sources and be partly responsible for the observed redshift distribution.[abridged]Comment: 33 pages, 21 figures, 3 tables ; accepted for publication in MNRA

    CHARACTERIZATION OF NEMOTIC DENTAL FIBROBLASTS

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    Oral Communication presented at the ";Forum des Jeunes Chercheurs";, Brest (France) 2011
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