We investigated some visual background features that influence young cuttlefish, Sepia pharaonis, to change their skin patterning from 'general resemblance' of the substratum to disruptive coloration that breaks up their body form. Using computer-generated black/white checkerboard patterns as substrata, we first found that the size of the white squares had to be within a certain narrow range (r...

Low-level mechanisms in vertebrate vision are sensitive to line orientation. Here we investigate orientation sensitivity in the cuttlefish Sepia pharaonis, by allowing animals to settle on stripe patterns. When camouflaging themselves cuttlefish are known to be sensitive to image parameters such as contrast and spatial scale, but we find no effect of background orientation on the patterns displ...

Modern cephalopods are notably the most intelligent invertebrates and this is accompanied by keen vision. Despite extensive studies investigating the visual systems of cephalopods, little is known about their visual perception and object recognition. In the present study, we investigated the visual processing of the cuttlefish Sepia pharaonis, including visual equivalence and amodal completion....

This paper describes SEPIA, a tool for automated proof generation in Coq. SEPIA combines model inference with interactive theorem proving. Existing proof corpora are modelled using state-based models inferred from tactic sequences. These can then be traversed automatically to identify proofs. The SEPIA system is described and its performance evaluated on three Coq datasets. Our results show tha...

Pharaonis halorhodopsin is a light-driven transport system for chloride, similarly to the previously described halorhodopsin, but we find that it transports nitrate as effectively as chloride. We studied the photoreactions of the purified, detergent-solubilized pharaonis pigment with a gated multichannel analyzer. At a physiological salt concentration (4 M NaCl), the absorption spectra and rate...

We present a new Machine Translation (MT) evaluation metric, SEPIA. SEPIA falls within the class of syntactically-aware evaluation metrics, which have been getting a lot of attention recently (Liu and Gildea, 2005; Owczarzak et al., 2007; Giménez and Màrquez, 2007). Specifically, SEPIA uses dependency representation but extends it to include surface span as a factor in the evaluation score. The...