579 research outputs found

    Usage of WordNet in Natural Language Generation

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    WordNet has rarely been applied to natural language generation, despite of its wide application in other fields. In this paper, we address three issues in the usage of WordNet in generation: adapting a general lexicon like WordNet to a specific application domain, how the information in WordNet can be used in generation, and augmenting WordNet with other types of knowledge that are helpful for generation. We propose a three step procedure to tailor WordNet to a specific domain, and carried out experiments on a basketball corpus (1,015 game reports, 1.7MB)

    Centroid-based summarization of multiple documents: sentence extraction, utility-based evaluation, and user studies

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    We present a multi-document summarizer, called MEAD, which generates summaries using cluster centroids produced by a topic detection and tracking system. We also describe two new techniques, based on sentence utility and subsumption, which we have applied to the evaluation of both single and multiple document summaries. Finally, we describe two user studies that test our models of multi-document summarization.Comment: 10 pages Corpus availability at http://perun.si.umich.edu/~radev/md

    Generating indicative-informative summaries with SumUM

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    We present and evaluate SumUM, a text summarization system that takes a raw technical text as input and produces an indicative informative summary. The indicative part of the summary identifies the topics of the document, and the informative part elaborates on some of these topics according to the reader's interest. SumUM motivates the topics, describes entities, and defines concepts. It is a first step for exploring the issue of dynamic summarization. This is accomplished through a process of shallow syntactic and semantic analysis, concept identification, and text regeneration. Our method was developed through the study of a corpus of abstracts written by professional abstractors. Relying on human judgment, we have evaluated indicativeness, informativeness, and text acceptability of the automatic summaries. The results thus far indicate good performance when compared with other summarization technologies

    Optimizing the thermoelectric performance of zigzag and chiral carbon nanotubes

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    Using nonequilibrium molecular dynamics simulations and nonequilibrium Green's function method, we investigate the thermoelectric properties of a series of zigzag and chiral carbon nanotubes which exhibit interesting diameter and chirality dependence. Our calculated results indicate that these carbon nanotubes could have higher ZT values at appropriate carrier concentration and operating temperature. Moreover, their thermoelectric performance can be significantly enhanced via isotope substitution, isoelectronic impurities, and hydrogen adsorption. It is thus reasonable to expect that carbon nanotubes may be promising candidates for high-performance thermoelectric materials

    Effective detection of seismic events by non-classical receptive field visual cognitive modelling.

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    The detection and up-picking of the seismic events are critical for seismic data analysis and interpretation. Events picking can be used for sequence stratigraphic analysis, reservoir feature extraction, the determining of the subsequent reflection interface, the improving of the SNR and the storage prediction. The research of the events picking is very significant for the seismic exploration. In order to overcome the existing events picking methods have the same sensitivity to noise, we propose a non-classical receptive field visual cognitive method for the events picking UP. Vision is an important functional organ for human beings to observe and recognize the world. About 80% of the information obtained by human beings from the outside world comes from the visual system, which fully shows that visual information is huge_ and also shows that human beings have a high utilization rate of visual information. How to transfer some typical information processing mechanism and target recognition function of human vision to machine is one of the most important and urgent tasks in the field of computer vision and artificial intelligence. The introduction of computer vision technology into geophysical prospecting is still in its infancy in the field of seismic exploration, our research fill the blank of this field, where the use of visual features to improve the seismic data processing and rapid realization of oil and gas exploration, will become the vane of the future direction of research and development. As a basic research work in the crossing field, this paper has made a breakthrough in the research methods and ideas, and the research content can be summarized as the following four aspects: 1. The proposed method implements the function of environmental suppression and spatial enhancement of the bio-visual primary visual cortex, which is applies to the ore-stack seismic data, as ore-stack seismic data contains abundant information such as amplitude and frequency to reflect tiny structures of the formation. 2. The seismic data is preprocessed to obtain the wavelet fusion of the envelope peak instantaneous frequency (EPIF) and the slant stack peak amplitude (SSPA), which can maximum the limit to provide optimal quality data. 3. An adaptive Gabor filter direction selection method is proposed to provide a reliable angle range and improve the recognition rate of filter decomposition. In addition. by adopting an anisotropic environmental suppression method, our method can detect edge variability more accurately than the isotropic method. 4. With the enhanced contour aggregation, cocircular constraint is adopted and combined with the characteristics of low curvature and continuous changing curvature, which is unique to the seismic events, to establish a consistent spatial structure perception model. The events picked by our method is more continuous and accurate than the existing methods, and doesn't require human interaction, which is beneficial for subsequent seismic interpretation and reservoir prediction

    Guanxintai Exerts Protective Effects on Ischemic Cardiomyocytes by Mitigating Oxidative Stress

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    Oxidative stress participates in numerous myocardial pathophysiological processes and is considered a therapeutic target for myocardial ischemia and heart failure. Guanxintai (GXT), a traditional Chinese medicine, is commonly used to treat cardiovascular disease on account of its numerous beneficial physiological activities, such as dilating coronary arteries, inhibiting platelet aggregation, and reducing the serum lipid content. However, the antioxidative properties of GXT and potential underlying mechanisms remain to be established. In the present study, we investigated the protective effects of GXT on ischemic cardiomyocytes and the associated antioxidative mechanisms, both in vivo and in vitro. Notably, GXT treatment reduced the degree of cardiomyocyte injury, myocardial apoptosis, and fibrosis and partially improved cardiac function after myocardial infarction. Furthermore, GXT suppressed the level of ROS as well as expression of NADPH oxidase (NOX) and phospho-p38 mitogen-activated protein kinase (MAPK) proteins. Our results collectively suggest that the protective effects of GXT on ischemic cardiomyocytes are exerted through its antioxidative activity of NOX inhibition

    Protective effect of grifolin against brain injury in an acute cerebral ischemia rat model

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    Purpose: To evaluate the protective effects of grifolin against brain injury in an acute cerebral ischemia rat model.Methods: Rats were assigned to five groups: control, negative control, and grifolin (50, 100, and 200 mg/kg, p.o.) treated groups, which received the drug for 2 weeks. All the animals were sacrificed at the end of the protocol, and tissue homogenates were prepared from isolated brain tissue. Glutathione peroxidase (GPX), superoxide dismutase (SOD), malondialdehyde (MDA), and nitric oxide (NO), as oxidative stress indicators, were determined for the tissue homogenates of the ischemic rats. Inflammatory mediators (cytokines and nuclear factor kappa B p65, NF κB), DNA damage, and ATP and caspase 3 levels in the tissue homogenates were also assessed.Results: Treatment with grifolin increased SOD and GPX significantly and decreased MDA and NO levels in tissue homogenates of the cerebral ischemic rats compared with those in the negative control group (p < 0.05). Treatment with grifolin also attenuated the altered levels of inflammatory mediators (cytokines and NF-κB), caspase 3, and ATP levels in the tissue homogenate of cerebral ischemic rats (p < 0.05). The results of comet assay on the tissue homogenate suggest that treatment with grifolin reduced or prevented damage.Conclusions: The results show that treatment with grifolin protects against neuronal damage in acute cerebral ischemic rats via its anti-inflammatory and anti-oxidant properties.Keywords: Neuroprotection, Cerebral ischemia, Brain injury, DNA, Grifolin, Anti oxidan
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