89 research outputs found

    Joint event extraction based on hierarchical event schemas from framenet

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    Event extraction is useful for many practical applications, such as news summarization and information retrieval. However, the popular automatic context extraction (ACE) event extraction program only defines very limited and coarse event schemas, which may not be suitable for practical applications. FrameNet is a linguistic corpus that defines complete semantic frames and frame-to-frame relations. As frames in FrameNet share highly similar structures with event schemas in ACE and many frames actually express events, we propose to redefine the event schemas based on FrameNet. Specifically, we extract frames expressing event information from FrameNet and leverage the frame-to-frame relations to build a hierarchy of event schemas that are more fine-grained and have much wider coverage than ACE. Based on the new event schemas, we propose a joint event extraction approach that leverages the hierarchical structure of event schemas and frame-to-frame relations in FrameNet. The extensive experiments have verified the advantages of our hierarchical event schemas and the effectiveness of our event extraction model. We further apply the results of our event extraction model on news summarization. The results show that the summarization approach based on our event extraction model achieves significant better performance than several state-of-the-art summarization approaches, which also demonstrates that the hierarchical event schemas and event extraction model are promising to be used in the practical applications

    What Makes it Difficult to Understand a Scientific Literature?

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    In the artificial intelligence area, one of the ultimate goals is to make computers understand human language and offer assistance. In order to achieve this ideal, researchers of computer science have put forward a lot of models and algorithms attempting at enabling the machine to analyze and process human natural language on different levels of semantics. Although recent progress in this field offers much hope, we still have to ask whether current research can provide assistance that people really desire in reading and comprehension. To this end, we conducted a reading comprehension test on two scientific papers which are written in different styles. We use the semantic link models to analyze the understanding obstacles that people will face in the process of reading and figure out what makes it difficult for human to understand a scientific literature. Through such analysis, we summarized some characteristics and problems which are reflected by people with different levels of knowledge on the comprehension of difficult science and technology literature, which can be modeled in semantic link network. We believe that these characteristics and problems will help us re-examine the existing machine models and are helpful in the designing of new one.Comment: Accepted by SKG201

    Intracranial electrophysiological recordings on a swine model of mesial temporal lobe epilepsy

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    ObjectiveTo test the feasibility and reliability of intracranial electrophysiological recordings in an acute status epilepticus model on laboratory swine.MethodIntrahippocampal injection of kainic acid (KA) was performed on 17 male Bama pigs (Sus scrofa domestica) weighing between 25 and 35 kg. Two stereoelectroencephalography (SEEG) electrodes with a total of 16 channels were implanted bilaterally along the sensorimotor cortex to the hippocampus. Brain electrical activity was recorded 2 h daily for 9–28 days. Three KA dosages were tested to evaluate the quantities capable of evoking status epilepticus. Local field potentials (LFPs) were recorded and compared before and after the KA injection. We quantified the epileptic patterns, including the interictal spikes, seizures, and high-frequency oscillations (HFOs), up to 4 weeks after the KA injection. Test–retest reliability using intraclass correlation coefficients (ICCs) were performed on interictal HFO rates to evaluate the recording stability of this model.ResultsThe KA dosage test suggested that a 10 μl (1.0 μg/μl) intrahippocampal injection could successfully evoke status epilepticus lasting from 4 to 12 h. At this dosage, eight pigs (50% of total) had prolonged epileptic events (tonic-chronic seizures + interictal spikes n = 5, interictal spikes alone n = 3) in the later 4 weeks of the video-SEEG recording period. Four pigs (25% of total) had no epileptic activities, and another four (25%) had lost the cap or did not complete the experiments. Animals that showed epileptiform events were grouped as E + (n = 8) and the four animals showing no signs of epileptic events were grouped as E– (n = 4). A total of 46 electrophysiological seizures were captured in the 4-week post-KA period from 4 E + animals, with the earliest onset on day 9. The seizure durations ranged from 12 to 45 s. A significant increase of hippocampal HFOs rate (num/min) was observed in the E+ group during the post-KA period (weeks 1, 2,4, p < 0.05) compared to the baseline. But the E-showed no change or a decrease (in week 2, p = 0.43) compared to their baseline rate. The between-group comparison showed much higher HFO rates in E + vs. E – (F = 35, p < 0.01). The high ICC value [ICC (1, k) = 0.81, p < 0.05] quantified from the HFO rate suggested that this model had a stable measurement of HFOs during the four-week post-KA periods.SignificanceThis study measured intracranial electrophysiological activity in a swine model of KA-induced mesial temporal lobe epilepsy (mTLE). Using the clinical SEEG electrode, we distinguished abnormal EEG patterns in the swine brain. The high test–retest reliability of HFO rates in the post-KA period suggests the utility of this model for studying mechanisms of epileptogenesis. The use of swine may provide satisfactory translational value for clinical epilepsy research

    White matter hyperintensities burden in the frontal regions is positively correlated to the freezing of gait in Parkinson’s disease

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    ObjectivePrevious studies have reported that white matter hyperintensities (WMHs) are associated with freezing of gait (FOG), but it is not clear whether their distribution areas have correlations with FOG in Parkinson’s disease (PD) and the potential influencing factors about WMHs.MethodsTwo hundred and forty-six patients with PD who underwent brain MRI were included. Participants were divided into PD with FOG (n = 111) and PD without FOG (n = 135) groups. Scheltens score was used to assess the WMHs burden in the areas of deep white matter hyperintensities (DWMHs), periventricular hyperintensities (PVHs), basal ganglia hyperintensities (BGHs), and infratentorial foci of hyperintensities (ITF). Whole brain WMHs volume was evaluated by automatic segmentation. Binary logistic regression was used to evaluate relationships between WMHs and FOG. The common cerebrovascular risk factors that may affect WMHs were evaluated by mediation analysis.ResultsThere were no statistical differences between PD with and without FOG groups in whole brain WMHs volume, total Scheltens score, BGHs, and ITF. Binary logistic regression showed that the total scores of DWMHs (OR = 1.094; 95% CI, 1.001, 1.195; p = 0.047), sum scores of PVHs and DWMHs (OR = 1.080; 95% CI, 1.003, 1.164; p = 0.042), especially the DWMHs in frontal (OR = 1.263; 95% CI, 1.060, 1.505 p = 0.009), and PVHs in frontal caps (OR = 2.699; 95% CI, 1.337, 5.450; p = 0.006) were associated with FOG. Age, hypertension, and serum alkaline phosphatase (ALP) are positively correlated with scores of DWMHs in frontal and PVHs in frontal caps.ConclusionThese results indicate that WMHs distribution areas especially in the frontal of DWMHs and PVHs play a role in PD patients with FOG

    Methyltransferase Dnmt3a upregulates HDAC9 to deacetylate the kinase TBK1 for activation of antiviral innate immunity

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    The DNA methyltransferase Dnmt3a has high expression in terminally differentiated macrophages; however, its role in innate immunity remains unknown. Here we report that deficiency in Dnmt3a selectively impaired the production of type I interferons triggered by pattern-recognition receptors (PRRs), but not that of the proinflammatory cytokines TNF and IL-6. Dnmt3a-deficient mice exhibited enhanced susceptibility to viral challenge. Dnmt3a did not directly regulate the transcription of genes encoding type I interferons; instead, it increased the production of type I interferons through an epigenetic mechanism by maintaining high expression of the histone deacetylase HDAC9. In turn, HDAC9 directly maintained the deacetylation status of the key PRR signaling molecule TBK1 and enhanced its kinase activity. Our data add mechanistic insight into the crosstalk between epigenetic modifications and post-translational modifications in the regulation of PRR signaling and activation of antiviral innate immune responses

    Investigation on the utilization of coal gasification slag in Portland cement: reaction kinetics and microstructure

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    Gasification slag is a solid waste generated by the coal chemical industry which has emerged in recent years. In this paper, the effect of coal gasification slag (CGS) powder content on the reaction kinetics, gel structure and the compressive strength of Portland cement was investigated for the potential application of CGS powders in cementitious materials. The reaction and gel structure of Portland cement blended with CGS was analyzed by using X-ray diffraction, Fourier transform infrared spectroscopy and scanning electron microscopy tests. The results show that the unreacted CGS power exists mainly in an agglomerated state in cement matrix, and a low dosage of CGS powder (10%) can play a role in nucleation and pozzolanic effect in Portland cement, which is conducive to the formation of hydration reactions of Portland cement, shortening the setting time and improving the compressive strength. If the CGS content is >30%, the hydration product content decreases, and the microstructure of the sample becomes loosened. The setting times are significantly prolonged with the increase of CGS content dosing and the compressive strength is considerably reduced as well

    Large-Scale Long-Term Prediction of Ship AIS Tracks via Linear Networks with a Look-Back Window Decomposition Scheme of Time Features

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    Approximating the positions of vessels near underwater devices, such as unmanned underwater vehicles and autonomous underwater vehicles, is crucial for many underwater operations. However, long-term monitoring of vessel trajectories is challenging due to limitations in underwater communications, posing challenges for the execution of underwater exploration missions. Therefore, trajectory prediction based on AIS data is vital in the fusion of underwater detection information. However, traditional models for underwater vessel trajectory prediction typically work well for only small-scale and short-term predictions. In this paper, a novel deep learning method is proposed that leverages a look-back window to decompose the temporal and motion features of ship movement trajectories, enabling long-term vessel prediction in broader sea areas. This research introduces an innovative model structure that enables trajectory features to be simultaneously learned for a larger range of vessels and facilitates long-term prediction. Through this innovative model design, the proposed model can more accurately predict vessel trajectories, providing reliable and comprehensive forecasting results. Our proposed model outperforms the Nlinear model by a 16% improvement in short-term prediction accuracy and an approximately 8% improvement in long-term prediction accuracy. The model also outperforms the Patch model by 5% in accuracy. In summary, the proposed method can produce competitive predictions for the long-term future trajectory trends of ships in large-scale sea areas

    Iron(III) reduction-induced phosphate precipitation during anaerobic digestion of waste activated sludge

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    Iron(III) reduction-induced phosphate precipitation during anaerobic digestion of waste activated sludge from a wastewater treatment plant was investigated for phosphorus removal and possible recovery. The digestion of sludge with Fe(III) amendments was performed in batch assays using hematite and ferrihydrite as the iron sources. Aqueous phosphate concentrations as high as 316 mg/L (as P) were observed in the Fe(III)-free controls after 30 d of digestion, demonstrating waste activated sludge to be an excellent material for phosphorus recovery. Ferrihydrite-Fe(III) was effectively reduced during the digestion, whereas the reduction of hematite-Fe(III) was insignificant. Phosphate removal in the Fe(III) amended sludge was closely related to the extent of Fe(III) reduction. Compared with the controls, 53% of aqueous phosphate in the ferrihydrite-amended sludge was removed as Fe(III) reduction occurred. The analyses of the phosphate and Fe(II) flows indicate that the removed aqueous phosphate was generally via Fe(II) bounded precipitates. (C) 2015 Elsevier B.V. All rights reserved
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