Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling

Semantic role labeling (SRL) is the task of identifying the predicate-argument structure of a sentence. It is typically regarded as an important step in the standard NLP pipeline. As the semantic representations are closely related to syntactic ones, we exploit syntactic information in our model. We propose a version of graph convolutional networks (GCNs), a recent class of neural networks operating on graphs, suited to model syntactic dependency graphs. GCNs over syntactic dependency trees are used as sentence encoders, producing latent feature representations of words in a sentence. We observe that GCN layers are complementary to LSTM ones: when we stack both GCN and LSTM layers, we obtain a substantial improvement over an already state-of-the-art LSTM SRL model, resulting in the best reported scores on the standard benchmark (CoNLL-2009) both for Chinese and English.Comment: To appear in EMNLP 201

The role of heat-flux–temperature covariance in the evolution of weather systems

Local diabatic heating and temperature anomaly fields need to be positively correlated for the diabatic heating to maintain a circulation against dissipation. Here we quantify the thermodynamic contribution of local air–sea heat exchange on the evolution of weather systems using an index of the spatial covariance between heat flux at the air–sea interface and air temperature at 850 hPa upstream of the North Atlantic storm track, corresponding with the Gulf Stream extension region. The index is found to be almost exclusively negative, indicating that the air–sea heat fluxes act locally as a sink on potential energy. It features bursts of high activity alternating with longer periods of lower activity. The characteristics of these high-index bursts are elucidated through composite analysis and the mechanisms are investigated in a phase space spanned by two different index components. It is found that the negative peaks in the index correspond with thermodynamic activity triggered by the passage of a weather system over a spatially variable sea-surface temperature field; our results indicate that most of this thermodynamically active heat exchange is realised within the cold sector of the weather systems

A Simple and Accurate Syntax-Agnostic Neural Model for Dependency-based Semantic Role Labeling

We introduce a simple and accurate neural model for dependency-based semantic role labeling. Our model predicts predicate-argument dependencies relying on states of a bidirectional LSTM encoder. The semantic role labeler achieves competitive performance on English, even without any kind of syntactic information and only using local inference. However, when automatically predicted part-of-speech tags are provided as input, it substantially outperforms all previous local models and approaches the best reported results on the English CoNLL-2009 dataset. We also consider Chinese, Czech and Spanish where our approach also achieves competitive results. Syntactic parsers are unreliable on out-of-domain data, so standard (i.e., syntactically-informed) SRL models are hindered when tested in this setting. Our syntax-agnostic model appears more robust, resulting in the best reported results on standard out-of-domain test sets.Comment: To appear in CoNLL 201

Therapeutic potential of co-enzyme Q10 in retinal diseases

Coenzyme Q10 (CoQ10) plays a critical role in mitochondrial oxidative phosphorylation by serving as an electron carrier in the respiratory electron transport chain. CoQ10 also functions as a lipid-soluble antioxidant by protecting lipids, proteins and DNA damaged by oxidative stress. CoQ10 deficiency has been associated with a number of human diseases including mitochondrial diseases, neurodegenerative disorders, cardiovascular diseases, diabetes, cancer, and with the ageing process. In many of these conditions CoQ10 supplementation therapy has been effective in slowing or reversing pathological changes. Oxidative stress is a major contributory factor in the process of retinal degeneration. In this brief review, we summarize the functions of CoQ10 and highlight its use in the treatment of age-related macular degeneration and glaucoma. In light of these data we propose that CoQ10 could have therapeutic potential for other retinal diseases