61 research outputs found

    General Stability Analysis of Synchronized Dynamics in Coupled Systems

    Full text link
    We consider the stability of synchronized states (including equilibrium point, periodic orbit or chaotic attractor) in arbitrarily coupled dynamical systems (maps or ordinary differential equations). We develop a general approach, based on the master stability function and Gershgorin disc theory, to yield constraints on the coupling strengths to ensure the stability of synchronized dynamics. Systems with specific coupling schemes are used as examples to illustrate our general method.Comment: 8 pages, 1 figur

    Discovery and integration of Web 2.0 content into geospatial information infrastructures: a use case in wild fire monitoring

    Get PDF
    Efficient environment monitoring has become a major concern for society to guarantee sustainable development. For instance, forest fire detection and analysis is important to provide early warning systems and identify impact. In this environmental context, availability of up-to-date information is very important for reducing damages caused. Environmental applications are deployed on top of GeospatialInformation Infrastructures (GIIs) to manage information pertaining to our environment. Suchinfrastructures are traditionally top-down infrastructures that do not consider user participation. This provokes a bottleneck in content publication and therefore a lack of content availability. On the contrary mainstream IT systems and in particular the emerging Web 2.0 Services allow active user participation that is becoming a massive source of dynamic geospatial resources. In this paper, we present a webservice, that implements a standard interface, offers a unique entry point for spatial data discovery, both in GII services and web 2.0 services. We introduce a prototype as proof of concept in a forest fire scenario, where we illustrate how to leverage scientific data and web 2.0 conten

    A weakly stable algorithm for general Toeplitz systems

    Full text link
    We show that a fast algorithm for the QR factorization of a Toeplitz or Hankel matrix A is weakly stable in the sense that R^T.R is close to A^T.A. Thus, when the algorithm is used to solve the semi-normal equations R^T.Rx = A^Tb, we obtain a weakly stable method for the solution of a nonsingular Toeplitz or Hankel linear system Ax = b. The algorithm also applies to the solution of the full-rank Toeplitz or Hankel least squares problem.Comment: 17 pages. An old Technical Report with postscript added. For further details, see http://wwwmaths.anu.edu.au/~brent/pub/pub143.htm

    To wet or not to wet: that is the question

    Full text link
    Wetting transitions have been predicted and observed to occur for various combinations of fluids and surfaces. This paper describes the origin of such transitions, for liquid films on solid surfaces, in terms of the gas-surface interaction potentials V(r), which depend on the specific adsorption system. The transitions of light inert gases and H2 molecules on alkali metal surfaces have been explored extensively and are relatively well understood in terms of the least attractive adsorption interactions in nature. Much less thoroughly investigated are wetting transitions of Hg, water, heavy inert gases and other molecular films. The basic idea is that nonwetting occurs, for energetic reasons, if the adsorption potential's well-depth D is smaller than, or comparable to, the well-depth of the adsorbate-adsorbate mutual interaction. At the wetting temperature, Tw, the transition to wetting occurs, for entropic reasons, when the liquid's surface tension is sufficiently small that the free energy cost in forming a thick film is sufficiently compensated by the fluid- surface interaction energy. Guidelines useful for exploring wetting transitions of other systems are analyzed, in terms of generic criteria involving the "simple model", which yields results in terms of gas-surface interaction parameters and thermodynamic properties of the bulk adsorbate.Comment: Article accepted for publication in J. Low Temp. Phy

    Cross-ancestry genome-wide association analysis of corneal thickness strengthens link between complex and Mendelian eye diseases

    Get PDF
    Central corneal thickness (CCT) is a highly heritable trait associated with complex eye diseases such as keratoconus and glaucoma. We perform a genome-wide association meta-analysis of CCT and identify 19 novel regions. In addition to adding support for known connective tissue-related pathways, pathway analyses uncover previously unreported gene sets. Remarkably, >20% of the CCT-loci are near or within Mendelian disorder genes. These included FBN1, ADAMTS2 and TGFB2 which associate with connective tissue disorders (Marfan, Ehlers-Danlos and Loeys-Dietz syndromes), and the LUM-DCN-KERA gene complex involved in myopia, corneal dystrophies and cornea plana. Using index CCT-increasing variants, we find a significant inverse correlation in effect sizes between CCT and keratoconus (r =-0.62, P = 5.30 × 10-5) but not between CCT and primary open-angle glaucoma (r =-0.17, P = 0.2). Our findings provide evidence for shared genetic influences between CCT and keratoconus, and implicate candidate genes acting in collagen and extracellular matrix regulation

    Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

    Get PDF
    Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations
    corecore