22 research outputs found

    Concepto, objeto y l铆mite de la ciencia econ贸mica

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    Understanding The Impact of Solver Choice in Model-Based Test Generation

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    Background: In model-based test generation, SMT solvers explore the state-space of the model in search of violations of specified properties. If the solver finds that a predicate can be violated, it produces a partial test specification demonstrating the violation.Aims: The choice of solvers is important, as each may produce differing counterexamples. We aim to understand how solver choice impacts the effectiveness of generated test suites at finding faults.Method: We have performed experiments examining the impact of solver choice across multiple dimensions, examining the ability to attain goal satisfaction and fault detection when satisfaction is achieved---varying the source of test goals, data types of model input, and test oracle.Results: The results of our experiment show that solvers vary in their ability to produce counterexamples, and---for models where all solvers achieve goal satisfaction---in the resulting fault detection of the generated test suites. The choice of solver has an impact on the resulting test suite, regardless of the oracle, model structure, or source of testing goals.Conclusions: The results of this study identify factors that impact fault-detection effectiveness, and advice that could improve future approaches to model-based test generation

    Necesidad de una asignatura filos贸fica en los planes de estudios de ciencias econ贸micas

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    Necesidad de una asignatura filos贸fica en los planes de estudios de ciencias econ贸micas

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    Combining clinical, pathology, and gene expression data to predict recurrence of hepatocellular carcinoma

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    Background & Aims In approximately 70% of patients with hepatocellular carcinoma (HCC) treated by resection or ablation, disease recurs within 5 years. Although gene expression signatures have been associated with outcome, there is no method to predict recurrence based on combined clinical, pathology, and genomic data (from tumor and cirrhotic tissue). We evaluated gene expression signatures associated with outcome in a large cohort of patients with early stage (Barcelona\u2013Clinic Liver Cancer 0/A), single-nodule HCC and heterogeneity of signatures within tumor tissues. Methods We assessed 287 HCC patients undergoing resection and tested genome-wide expression platforms using tumor (n = 287) and adjacent nontumor, cirrhotic tissue (n = 226). We evaluated gene expression signatures with reported prognostic ability generated from tumor or cirrhotic tissue in 18 and 4 reports, respectively. In 15 additional patients, we profiled samples from the center and periphery of the tumor, to determine stability of signatures. Data analysis included Cox modeling and random survival forests to identify independent predictors of tumor recurrence. Results Gene expression signatures that were associated with aggressive HCC were clustered, as well as those associated with tumors of progenitor cell origin and those from nontumor, adjacent, cirrhotic tissues. On multivariate analysis, the tumor-associated signature G3-proliferation (hazard ratio [HR], 1.75; P = .003) and an adjacent poor-survival signature (HR, 1.74; P = .004) were independent predictors of HCC recurrence, along with satellites (HR, 1.66; P = .04). Samples from different sites in the same tumor nodule were reproducibly classified. Conclusions We developed a composite prognostic model for HCC recurrence, based on gene expression patterns in tumor and adjacent tissues. These signatures predict early and overall recurrence in patients with HCC, and complement findings from clinical and pathology analyses

    Structural Properties for Deductive Argument Systems

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    There have been a number of proposals for using deductive arguments for instantiating abstract argumentation. These take a set of formulae as a knowledgebase, and generate a graph where each node is a logical argument and each arc is a logical attack. This then raises the question of whether for a specific logical argument system S, and for any graph G, there is a knowledgebase such that S generates G. If it holds, then it can be described as a kind of "structural" property of the system. If it fails then, it means that there are situations that cannot be captured by the system. In this paper, we explore some features, and the significance, of such structural properties. 漏 2013 Springer-Verlag Berlin Heidelberg
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