We propose a Dynamical Boolean Network (DBN), which is a Boolean network whose set of states is fixed but whose transition matrix can change from one discrete time step to another. At any time step, the transition matrix of our DBN is of the formQ−1TQ, where T is a transition matrix defined in the course of the construction of our DBN and Q is the matrix representation of some permutation P of ...

We describe SLING, a framework for parsing natural language into semantic frames. SLING supports general transition-based, neural-network parsing with bidirectional LSTM input encoding and a Transition Based Recurrent Unit (TBRU) for output decoding. The parsing model is trained end-to-end using only the text tokens as input. The transition system has been designed to output frame graphs direct...

Transition metal transporters are of central importance in the plant metal homeostasis network which maintains internal metal concentrations within physiological limits. An overview is given of the functions of known transition metal transporters in the context of the unique chemical properties of their substrates. The modifications of the metal homeostasis network associated with the adaptatio...

We use minority game model to investigate evolutionary dynamics in complex networks of adaptive agents competing for limited resources. We show that the dynamics and the phase structures critically depend on the underlying network organizations, and evolution is a key mechanism for the emergence of high-order coordination among the networked agents. A non-growing random directed network admits ...

An approximate representation for the state space of a context-sensitive probabilistic Boolean network has previously been proposed and utilized to devise therapeutic intervention strategies. Whereas the full state of a context-sensitive probabilistic Boolean network is specified by an ordered pair composed of a network context and a gene-activity profile, this approximate representation collap...

We propose a neural network model for scalable generative transition-based dependency parsing. A probability distribution over both sentences and transition sequences is parameterised by a feedforward neural network. The model surpasses the accuracy and speed of previous generative dependency parsers, reaching 91.1% UAS. Perplexity results show a strong improvement over n-gram language models, ...

In this paper we describe the results that came out from the project of employing the IPv6 protocol over the Greek Research & Technology Network (GRNET). In the way of this process one of the big issues that had to be considered was the transition strategy that would be deployed. The main goals of a transition strategy are to be smooth enough and therefore to put the less of configuration overh...

Different approaches for the transition between two coplanar waveguides of different characteristic impedances have been investigated to improve the efficiency of both feeding network and the antenna element of an antenna system operating in the Xband. Return loss, effect of feed line shaping and parametric study are presented with each approach. The outcomes of this study leads to efficient tr...

We study a coevolution voter model on a complex network. A mean-field approximation reveals an absorbing transition from an active to a frozen phase at a critical value [see text for formula] that only depends on the average degree micro of the network. In finite-size systems, the active and frozen phases correspond to a connected and a fragmented network, respectively. The transition can be se...

A performance evaluation of a crossbar network is presented using discrete-time Markov chain (MC). Identical processors, totally synchronized with system clock and communicating through common memory modules. Simple MC models the behavior of each processor. We have developed state and output equations for discrete-time state space model. The transition probabilities of transition matrices are c...