184 research outputs found

    Neural-symbolic probabilistic argumentation machines

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    Neural-symbolic systems combine the strengths of neural networks and symbolic formalisms. In this paper, we introduce a neural-symbolic system which combines restricted Boltzmann machines and probabilistic semi-abstract argumentation. We propose to train networks on argument labellings explaining the data, so that any sampled data outcome is associated with an argument labelling. Argument labellings are integrated as constraints within restricted Boltzmann machines, so that the neural networks are used to learn probabilistic dependencies amongst argument labels. Given a dataset and an argumentation graph as prior knowledge, for every example/case K in the dataset, we use a so-called K- maxconsistent labelling of the graph, and an explanation of case K refers to a K-maxconsistent labelling of the given argumentation graph. The abilities of the proposed system to predict correct labellings were evaluated and compared with standard machine learning techniques. Experiments revealed that such argumentation Boltzmann machines can outperform other classification models, especially in noisy settings

    Cytotoxic activity of the sub-fraction 2125 from Vernonia scorpioides against Sarcoma 180 tumor cells in mice

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    The effect of the selected sub-fraction SF-2125 of the Vernonia scorpioides leaf extract on Sarcoma 180 (S180) ascitic tumor-bearing mice was investigated. The animals were treated with SF-2125 at a concentration of 5 mg/kg, administered intraperitoneally and intravenous during the development of the tumor. Treatment with SF-2125 5 mg/kg i.p. increased the lifespan of the animals, maintained their body and the ascitic tumor showed no development. Intravenous treatment did not reduce the tumor volume

    Parallaxes of southern extremely cool objects III : 118 L and T dwarfs

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    We present new results from the Parallaxes of Southern Extremely Cool dwarfs program to measure parallaxes, proper motions and multiepoch photometry of L and early T dwarfs. The observations were made on 108 nights over the course of 8 yr using the Wide Field Imager on the ESO 2.2m telescope. We present 118 new parallaxes of L and T dwarfs of which 52 have no published values and 24 of the 66 published values are preliminary estimates from this program. The parallax precision varies from 1.0 to 15.5mas with a median of 3.8mas. We find evidence for two objects with long term photometric variation and 24 new moving group candidates. We cross-match our sample to published photometric catalogues and find standard magnitudes in up to 16 pass-bands from which we build spectral energy distributions and H-R diagrams. This allows us to confirm the theoretically anticipated minimum in radius between stars and brown dwarfs across the hydrogen burning minimum mass. We find the minimum occurs between L2 and L6 and verify the predicted steep dependence of radius in the hydrogen burning regime and the gentle rise into the degenerate brown dwarf regime. We find a relatively young age of ~2 Gyr from the kinematics of our sample.Peer reviewedFinal Accepted Versio
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