23 research outputs found

    Towards Transformation Rule Composition

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    Many model transformation problems require different intermediate transformation steps. For example, platform-specific models (PSM) are often generated from platform-independent models (PIM) by chains of model transformations. This requires the presence of several intermediate meta-models between those of the PIM and the PSM. Thus, most of the effort is needed to define a transformation mechanism for each intermediate step. The solution proposed in this paper is to investigate whether it is possible to generate a single transformation from a chain of transformations, solely involving the initial PIM and final PSM meta-models. The presented work focuses on the composition of transformations at the rule level. We apply the automatic procedure for composing rules in the context of the evolution of the Enterprise Java Beans (EJB) language, transforming UML models into EJB 2.0 models and then to EJB 3.0 models

    Automated Verification by Declarative Description of Graph Rewriting-Based Model Transformations

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    Usually, verification of graph rewriting-based model transformations is performed manually, however, the industrial applications require automated methods. In several cases, transformation developers are interested in the offline analysis, when only the definition of the transformation and the specification of the modeling languages are taken into account. Hence, the analysis must be performed only once, and the results are independent from the concrete input models. For this purpose, transformations should be specified in a formalism that can be automatically analyzed. Based on our previous work that presented the mathematical background, this paper provides a platform-independent, declarative formalism for the specification of graph rewriting-based model transformations, and demonstrates its applicability on a case study of refactoring mobile-based social network models. Our results prove that several functional properties of the model transformations can be automatically verified, moreover, the capabilities of our methods can be extended in the future

    LSST Science Book, Version 2.0

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    A survey that can cover the sky in optical bands over wide fields to faint magnitudes with a fast cadence will enable many of the exciting science opportunities of the next decade. The Large Synoptic Survey Telescope (LSST) will have an effective aperture of 6.7 meters and an imaging camera with field of view of 9.6 deg^2, and will be devoted to a ten-year imaging survey over 20,000 deg^2 south of +15 deg. Each pointing will be imaged 2000 times with fifteen second exposures in six broad bands from 0.35 to 1.1 microns, to a total point-source depth of r~27.5. The LSST Science Book describes the basic parameters of the LSST hardware, software, and observing plans. The book discusses educational and outreach opportunities, then goes on to describe a broad range of science that LSST will revolutionize: mapping the inner and outer Solar System, stellar populations in the Milky Way and nearby galaxies, the structure of the Milky Way disk and halo and other objects in the Local Volume, transient and variable objects both at low and high redshift, and the properties of normal and active galaxies at low and high redshift. It then turns to far-field cosmological topics, exploring properties of supernovae to z~1, strong and weak lensing, the large-scale distribution of galaxies and baryon oscillations, and how these different probes may be combined to constrain cosmological models and the physics of dark energy.Comment: 596 pages. Also available at full resolution at http://www.lsst.org/lsst/sciboo

    Nevirapine and Efavirenz Elicit Different Changes in Lipid Profiles in Antiretroviral- Therapy-Naive Patients Infected with HIV-1

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    BACKGROUND: Patients infected with HIV-1 initiating antiretroviral therapy (ART) containing a non-nucleoside reverse transcriptase inhibitor (NNRTI) show presumably fewer atherogenic lipid changes than those initiating most ARTs containing a protease inhibitor. We analysed whether lipid changes differed between the two most commonly used NNRTIs, nevirapine (NVP) and efavirenz (EFV). METHODS AND FINDINGS: Prospective analysis of lipids and lipoproteins was performed in patients enrolled in the NVP and EFV treatment groups of the 2NN study who remained on allocated treatment during 48 wk of follow-up. Patients were allocated to NVP (n = 417), or EFV (n = 289) in combination with stavudine and lamivudine. The primary endpoint was percentage change over 48 wk in high-density lipoprotein cholesterol (HDL-c), total cholesterol (TC), TC:HDL-c ratio, non-HDL-c, low-density lipoprotein cholesterol, and triglycerides. The increase of HDL-c was significantly larger for patients receiving NVP (42.5%) than for patients receiving EFV (33.7%; p = 0.036), while the increase in TC was lower (26.9% and 31.1%, respectively; p = 0.073), resulting in a decrease of the TC:HDL-c ratio for patients receiving NVP (−4.1%) and an increase for patients receiving EFV (+5.9%; p < 0.001). The increase of non-HDL-c was smaller for patients receiving NVP (24.7%) than for patients receiving EFV (33.6%; p = 0.007), as were the increases of triglycerides (20.1% and 49.0%, respectively; p < 0.001) and low-density lipoprotein cholesterol (35.0% and 40.0%, respectively; p = 0.378). These differences remained, or even increased, after adjusting for changes in HIV-1 RNA and CD4+ cell levels, indicating an effect of the drugs on lipids over and above that which may be explained by suppression of HIV-1 infection. The increases in HDL-c were of the same order of magnitude as those seen with the use of the investigational HDL-c-increasing drugs. CONCLUSION: NVP-containing ART shows larger increases in HDL-c and decreases in TC:HDL-c ratio than an EFV-containing regimen. Based on these findings, protease-inhibitor-sparing regimens based on non-nucleoside reverse transcriptase inhibitor, particularly those containing NVP, may be expected to result in a reduced risk of coronary heart disease
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