E-cigarette puffing patterns associated with high and low nicotine e-liquid strength: effects on toxicant and carcinogen exposure

Contrary to intuition, use of lower strength nicotine e-liquids might not offer reduced health risk if compensatory puffing behaviour occurs. Compensatory puffing (e.g. more frequent, longer puffs) or user behaviour (increasing the wattage) can lead to higher temperatures at which glycerine and propylene glycol (solvents used in e-liquids) undergo decomposition to carbonyl compounds, including the carcinogens formaldehyde and acetaldehyde. This study aims to document puffing patterns and user behaviour associated with using high and low strength nicotine e-liquid and associated toxicant/carcinogen exposure in experienced e-cigarette users (known as vapers herein).

A comparison of sound localisation techniques using cross-correlation and spiking neural networks for mobile robotics

This paper outlines the development of a crosscorrelation algorithm and a spiking neural network (SNN) for sound localisation based on real sound recorded in a noisy and dynamic environment by a mobile robot. The SNN architecture aims to simulate the sound localisation ability of the mammalian auditory pathways by exploiting the binaural cue of interaural time difference (ITD). The medial superior olive was the inspiration for the SNN architecture which required the integration of an encoding layer which produced biologically realistic spike trains, a model of the bushy cells found in the cochlear nucleus and a supervised learning algorithm. The experimental results demonstrate that biologically inspired sound localisation achieved using a SNN can compare favourably to the more classical technique of cross-correlation.