Understanding the three-dimensional variability of unidirectional composites is relevant to material performance and development advanced modelling strategies. This work proposes a new methodology for characterization composites, showcased on carbon fibre/poly(ether-ether-ketone) tapes. Three microstructural descriptors were here introduced, each representing an increasing level complexity in f...

A nonlinear type open-plus-closed-loop (OPCL) coupling is investigated for antisynchronization of two complex networks under unidirectional and bidirectional interactions where each node of the networks is considered as a continuous dynamical system. We present analytical results for antisynchronization in identical networks. A numerical example is given for unidirectional coupling with each no...

The suppressor of Hairy-wing [su(Hw)] protein represses enhancer function in a unidirectional fashion: enhancers segregated from the promoter by the su(Hw) binding region are rendered inactive. whereas those in the same domain are unaffected. In the case of the gypsy-induced y2 allele, the repressive effect of su(Hw) is rendered bidirectional in mod(mdg4) mutant flies, and all enhancers of the ...

This paper is motivated by the observation that current research in ad hoc networks mostly assumes a physically flat network architecture with the nodes having homogeneous characteristics, roles, and networkingand processingcapabilities (e.g., network resources, computing power, and transmission power). In real-world ad hoc networks however, node heterogeneity is inherent. New mechanisms at the...

We introduce a non-parity-time-symmetric three-layer structure, consisting of a gain medium layer sandwiched between two phase-change medium layers for switching of the direction of reflectionless light propagation. We show that for this structure unidirectional reflectionlessness in the forward direction can be switched to unidirectional reflectionlessness in the backward direction at the opti...

Recurrent neural networks (RNNs) have been shown to be very effective for many sequential prediction problems such as speech recognition, machine translation, part-of-speech tagging, and others. The best variant is typically a bidirectional RNN that learns representation for a sequence by performing a forward and a backward pass through the entire sequence. However, unlike unidirectional RNNs, ...