The uniqueness of signature problem in the non-Markov setting

We establish a general framework for a class of multidimensional stochastic processes over [0,1] under which with probability one, the signature (the collection of iterated path integrals in the sense of rough paths) is well-defined and determines the sample paths of the process up to reparametrization. In particular, by using the Malliavin calculus we show that our method applies to a class of Gaussian processes including fractional Brownian motion with Hurst parameter H>1/4, the Ornstein–Uhlenbeck process and the Brownian bridge.

Colloidal gas aphrons based separation process for the purification and fractionation of natural phenolic extracts

Following previous studies, the aim of this work is to further investigate the application of colloidal gas aphrons (CGA) to the recovery of polyphenols from a grape marc ethanolic extract with particular focus on exploring the use of a non-ionic food grade surfactant (Tween 20) as an alternative to the more toxic cationic surfactant CTAB. Different batch separation trials in a flotation column were carried out to evaluate the influence of surfactant type and concentration and processing parameters (such as pH, drainage time, CGA/extract volumetric and molar ratio) on the recovery of total and specific phenolic compounds. The possibility of achieving selective separation and concentration of different classes of phenolic compounds and non-phenolic compounds was also assessed, together with the influence of the process on the antioxidant capacity of the recovered compounds. The process led to good recovery, limited loss of antioxidant capacity, but low selectivity under the tested conditions. Results showed the possibility of using Tween 20 with a separation mechanism mainly driven by hydrophobic interactions. Volumetric ratio rather than the molar ratio was the key operating parameter in the recovery of polyphenols by CGA.

Creating a non-word list to match 226 of the Snodgrass standardised picture set

Creating non-word lists is a necessary but time consuming exercise often needed when conducting behavioural language tasks involving lexical decision-making or non-word reading. The following article describes the process whereby we created a list of 226 non-words matching 226 of the Snodgrass picture set (Snodgrass & Vanderwart, 1980).The non-words were matched for number of syllables, stress pattern, number of phonemes, bigram count and presence and location of the target sound when relevant.