Anomalous relaxation and self-organization in non-equilibrium processes

We study thermal relaxation in ordered arrays of coupled nonlinear elements with external driving. We find, that our model exhibits dynamic self-organization manifested in a universal stretched-exponential form of relaxation. We identify two types of self-organization, cooperative and anti-cooperative, which lead to fast and slow relaxation, respectively. We give a qualitative explanation for the behavior of the stretched exponent in different parameter ranges. We emphasize that this is a system exhibiting stretched-exponential relaxation without explicit disorder or frustration.Comment: submitted to PR

Wolves at SemEval-2018 Task 10: Semantic Discrimination based on Knowledge and Association

This paper describes the system submitted to SemEval 2018 shared task 10 ���Capturing Discriminative Attributes���. We use a combination of knowledge-based and co-occurrence features to capture the semantic difference between two words in relation to an attribute. We define scores based on association measures, ngram counts, word similarity, and ConceptNet relations. The system is ranked 4th (joint) on the official leaderboard of the task.Research Group in Computational Linguistic

Bridging the gap: Attending to discontinuity in identification of multiword expressions

We introduce a new method to tag Multiword Expressions (MWEs) using a linguistically interpretable language-independent deep learning architecture. We specifically target discontinuity, an under-explored aspect that poses a significant challenge to computational treatment of MWEs. Two neural architectures are explored: Graph Convolutional Network (GCN) and multi-head self-attention. GCN leverages dependency parse information, and self-attention attends to long-range relations. We finally propose a combined model that integrates complementary information from both through a gating mechanism. The experiments on a standard multilingual dataset for verbal MWEs show that our model outperforms the baselines not only in the case of discontinuous MWEs but also in overall F-score

The Application of Constraint Rules to Data-driven Parsing

In this paper, we show an approach to extracting different types of constraint rules from a dependency treebank. Also, we show an approach to integrating these constraint rules into a dependency data-driven parser, where these constraint rules inform parsing decisions in specific situations where a set of parsing rule (which is induced from a classifier) may recommend several recommendations to the parser. Our experiments have shown that parsing accuracy could be improved by using different sets of constraint rules in combination with a set of parsing rules. Our parser is based on the arc-standard algorithm of MaltParser but with a number of extensions, which we will discuss in some detail

Intelligent text processing to help readers with autism

© 2018, Springer International Publishing AG. Autistic Spectrum Disorder (ASD) is a neurodevelopmental disorder which has a life-long impact on the lives of people diagnosed with the condition. In many cases, people with ASD are unable to derive the gist or meaning of written documents due to their inability to process complex sentences, understand non-literal text, and understand uncommon and technical terms. This paper presents FIRST, an innovative project which developed language technology (LT) to make documents more accessible to people with ASD. The project has produced a powerful editor which enables carers of people with ASD to prepare texts suitable for this population. Assessment of the texts generated using the editor showed that they are not less readable than those generated more slowly as a result of onerous unaided conversion and were significantly more readable than the originals. Evaluation of the tool shows that it can have a positive impact on the lives of people with ASD.Published versio

Correlations between structure and dynamics in complex networks

Previous efforts in complex networks research focused mainly on the topological features of such networks, but now also encompass the dynamics. In this Letter we discuss the relationship between structure and dynamics, with an emphasis on identifying whether a topological hub, i.e. a node with high degree or strength, is also a dynamical hub, i.e. a node with high activity. We employ random walk dynamics and establish the necessary conditions for a network to be topologically and dynamically fully correlated, with topological hubs that are also highly active. Zipf's law is then shown to be a reflection of the match between structure and dynamics in a fully correlated network, as well as a consequence of the rich-get-richer evolution inherent in scale-free networks. We also examine a number of real networks for correlations between topology and dynamics and find that many of them are not fully correlated.Comment: 16 pages, 7 figures, 1 tabl

Helicoidal instability of a scroll vortex in three-dimensional reaction-diffusion systems

We study the dynamics of scroll vortices in excitable reaction-diffusion systems analytically and numerically. We demonstrate that intrinsic three-dimensional instability of a straight scroll leads to the formation of helicoidal structures. This behavior originates from the competition between the scroll curvature and unstable core dynamics. We show that the obtained instability persists even beyond the meander core instability of two-dimensional spiral wave.Comment: 4 pages, 5 figures, revte