Background: The effectiveness of tax increases in reducing tobacco consumption relies on the tobacco retailers and producers passing on increases to consumers (tax pass-through). Previous UK research on supermarkets found heterogeneous levels of tax pass-through across the market segments and price distribution of tobacco products. This study uses data from small retailers across the UK to assess whether recent tax changes have been passed on to consumers and if this varies across the price distribution, between countries of the UK and by neighbourhood deprivation.
View Article and Find Full Text PDFIndividuals who sustain a concussion can experience a range of symptoms which can significantly impact their quality of life and functional outcome. This study aims to understand the nature and recovery trajectories of post-concussion symptomatology by applying an unsupervised machine learning approach to data captured from a digital health intervention (HeadOn). As part of the 35-day program, patients complete a daily symptom diary which rates 8 post-concussion symptoms.
View Article and Find Full Text PDFWe present simulation results for the Donnan equilibrium between a homogeneous bulk reservoir and inhomogeneous confining geometries with varying number of restricted dimensions, . Planar slits ( = 1), cylindrical pores ( = 2), and spherical cavities ( = 3) are considered. The walls have a negative surface charge density.
View Article and Find Full Text PDFBiomacromolecular networks with multiscale fibrillar structures are characterized by exceptional mechanical properties, making them attractive architectures for synthetic materials. However, there is a dearth of synthetic polymeric building blocks capable of forming similarly structured networks. Bottlebrush polymers (BBPs) are anisotropic graft polymers with the potential to mimic and replace biomacromolecules such as tropocollagen for the fabrication of synthetic fibrillar networks; however, a longstanding limitation of BBPs has been the lack of rigidity necessary to access the lyotropic ordering that underpins the formation of collagenous networks.
View Article and Find Full Text PDFPassive acoustic monitoring (PAM) is an increasingly popular tool to study vocalising species. The amount of data generated by PAM studies calls for robust automatic classifiers. Deep learning (DL) techniques have been proven effective in identifying acoustic signals in challenging datasets, but due to their black-box nature their underlying biases are hard to quantify.
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