655 research outputs found

    A database management capability for Ada

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    The data requirements of mission critical defense systems have been increasing dramatically. Command and control, intelligence, logistics, and even weapons systems are being required to integrate, process, and share ever increasing volumes of information. To meet this need, systems are now being specified that incorporate data base management subsystems for handling storage and retrieval of information. It is expected that a large number of the next generation of mission critical systems will contain embedded data base management systems. Since the use of Ada has been mandated for most of these systems, it is important to address the issues of providing data base management capabilities that can be closely coupled with Ada. A comprehensive distributed data base management project has been investigated. The key deliverables of this project are three closely related prototype systems implemented in Ada. These three systems are discussed

    Towards automated restructuring of object oriented systems

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    The work introduces a method for diagnosing design flaws in object oriented systems, and finding meaningful refactorings to remove such flaws. The method is based on pairing up a structural pattern that is considered pathological (e.g. a code smell or anti-pattern) with a so called design context. The design context describes the design semantics associated to the pathological structure, and the desired strategic closure for that fragment. The process is tool supported and largely automated

    A database model for object dynamics.

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    Object-oriented database systems, Dynamic object re-classification, Object role model, Dynamic class hierarchy, Object migration

    Reverse engineering of model transformations for reusability

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    The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-08789-4_14Proceedings of 7th International Conference, ICMT 2014, Held as Part of STAF 2014, York, UK, July 21-22, 2014Reuse techniques are key for the industrial adoption of Model-Driven Engineering (MDE). However, while reusability has been successfully applied to programming languages, its use is scarce in MDE and, in particular, in model transformations. In previous works, we developed an approach that enables the reuse of model transformations for different meta-models. This is achieved by defining reusable components that encapsulate a generic transformation template and expose an interface called concept declaring the structural requirements that any meta-model using the component should fulfil. Binding the concept to one of such meta-models induces an adaptation of the template, which becomes applicable to the meta-model. To facilitate reuse, concepts need to be concise, reflecting only the minimal set of requirements demanded by the transformation. In this paper, we automate the reverse engineering of existing transformations into reusable transformation components. To make a transformation reusable, we use the information obtained from its static analysis to derive a concept that is minimal with respect to the transformation and maximizes its reuse opportunities, and then evolve the transformation accordingly. The paper describes a prototype implementation and an evaluation using transformations from the ATL zoo.This work has been funded by the Spanish Ministry of Economy and Competitivity with project “Go Lite” (TIN2011-24139

    Epithelial-mesenchymal transition and cancer stem cells: a dangerously dynamic duo in breast cancer progression

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    Aberrant activation of a latent embryonic program - known as the epithelial-mesenchymal transition (EMT) - can endow cancer cells with the migratory and invasive capabilities associated with metastatic competence. The induction of EMT entails the loss of epithelial characteristics and the de novo acquisition of a mesenchymal phenotype. In breast cancer, the EMT state has been associated with cancer stem cell properties including expression of the stem cell-associated CD44+/CD24-/low antigenic profile, self-renewal capabilities and resistance to conventional therapies. Intriguingly, EMT features are also associated with stem cells isolated from the normal mouse mammary gland and human breast reduction tissues as well as the highly aggressive metaplastic and claudin-low breast tumor subtypes. This has implications for the origin of these breast tumors as it remains unclear whether they derive from cells that have undergone EMT or whether they represent an expansion of a pre-existing stem cell population that expresses EMT-associated markers to begin with. In the present review, we consider the current evidence connecting EMT and stem cell attributes and discuss the ramifications of these newly recognized links for our understanding of the emergence of distinct breast cancer subtypes and breast cancer progression

    Programming Languages for Scientific Computing

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    Scientific computation is a discipline that combines numerical analysis, physical understanding, algorithm development, and structured programming. Several yottacycles per year on the world's largest computers are spent simulating problems as diverse as weather prediction, the properties of material composites, the behavior of biomolecules in solution, and the quantum nature of chemical compounds. This article is intended to review specfic languages features and their use in computational science. We will review the strengths and weaknesses of different programming styles, with examples taken from widely used scientific codes.Comment: 21 page

    Identifying the Cell Composition and Clonal Diversity of Supratentorial Ependymoma Using Single Cell RNA-Sequencing

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    Ependymoma is a primary solid tumor of the central nervous system. Supratentorial ependymoma (ST-EPN), a subtype of ependymomas, is driven by an oncogenic fusion between the ZFTA and RELA genes in 70% of cases. We introduced this fusion into neural progenitor cells of mice embryos via in utero electroporation of a non-viral binary piggyBac transposon system containing ZFTA-RELA. From preliminary data in the LoTurco lab, inducing the expression of ZFTA-RELA into different neural progenitor cells produces tumors of varying lethality and cellular composition. To define the cellular composition and subclonal diversity of ST-EPN tumors, we used single cell RNA-sequencing to derive a transcriptomic profile of the heterogeneous cell types composing ST-EPN mouse tumors. Among the 20,000 cells sequenced, approximately two-thirds of the cells did not express the oncogene. These cells represent various types of immune cells, such as B-lymphocytes, T-cells, and macrophages; stromal cells, and different neural cell types (i.e. oligodendrocytes). Although ZFTA-RELA has been shown to activate NF-ÎșB effector genes, there was not a ubiquitous upregulation of such genes across the cells enriched for ZFTA-RELA expression. Subclustering these tumorigenic cells revealed distinct subpopulations characterized by upregulation of non-NFÎșB pathways involved in cell proliferation, extracellular environment reorganization, and immune activation. We identified a list of specific markers for these cellular conditions to better characterize the processes underlying ST-EPN aggressiveness and immunological responses
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