Description: Microseisms in the period of 2–10 s are generated in deep oceans and near coastal regions. It is common for microseisms from multiple sources to arrive at the same time at a given seismometer. It is therefore desirable to be able to measure multiple slowness vectors accurately. Popular ways to estimate the direction of arrival of ocean induced microseisms are the conventional (fk) or adaptive (Capon) beamformer. These techniques give robust estimates, but are limited in their resolution capabilities and hence do not always detect all arrivals. One of the limiting factors in determining direction of arrival with seismic arrays is the array response, which can strongly influence the estimation of weaker sources. In this work, we aim to improve the resolution for weaker sources and evaluate the performance of two deconvolution algorithms, Richardson–Lucy deconvolution and a new implementation of CLEAN-PSF. The algorithms are tested with three arrays of different aperture (ASAR, WRA and NORSAR) using 1 month of real data each and compared with the conventional approaches. We find an improvement over conventional methods from both algorithms and the best performance with CLEAN-PSF. We then extend the CLEAN-PSF framework to three components (3C) and evaluate 1 yr of data from the Pilbara Seismic Array in northwest Australia. The 3C CLEAN-PSF analysis is capable in resolving a previously undetected Sn phase.

Description: Background To understand attitudes and behaviours of adolescents towards antibiotics, antimicrobial resistance and respiratory tract infections. Design Qualitative approach informed by the Theory of Planned Behaviour. Semi-structured interviews and focus groups were undertaken. We aimed to inform the development of an intervention in an international setting to improve antibiotic use among adolescents; therefore on completion of thematic analysis, findings were triangulated with qualitative data from similar studies in France, Saudi Arabia and Cyprus to elucidate differences in the behaviour change model and adaptation to diverse contexts. Setting 7 educational establishments from the south of England. Participants 53 adolescents (16–18 years) participated in seven focus groups and 21 participated in interviews. Results Most participants had taken antibiotics and likened them to other common medications such as painkillers; they reported that their peers treat antibiotics like a ‘cure-all’ and that they themselves were not interested in antibiotics as a discussion topic. They demonstrated low knowledge of the difference between viral and bacterial infections.Participants self-cared for colds and flu but believed antibiotics are required to treat other RTIs such as tonsillitis, which they perceived as more ‘serious’. Past history of taking antibiotics for RTIs instilled the belief that antibiotics were required for future RTIs. Those who characterised themselves as ‘non-science students’ were less informed about antibiotics and AMR. Most participants felt that AMR was irrelevant to them and their peers. Some ‘non-science’ students thought resistance was a property of the body, rather than bacteria. Conclusion Addressing adolescents’ misperceptions about antibiotics and the treatment of RTIs using a behaviour change intervention should help improve antibiotic awareness and may break the cycle of patient demand for antibiotics to treat RTIs amongst this group. Schools should consider educating all students in further education about antibiotic usage and AMR, not only those taking science.

Description: Genetic diseases are both inherited and acquired. Many genetic diseases fall under the paradigm of orphan diseases, a disease found in 〈 1 in 2000 persons. With rapid and cost-effective genome sequencing becoming the norm, many causal mutations for genetic diseases are being rapidly determined. In this regard, model organisms are playing an important role in validating if specific mutations identified in patients drive the observed phenotype. An emerging challenge for model organism researchers is the application of genetic and chemical genetic platforms to discover drug targets and drugs/drug-like molecules for potential treatment options for patients with genetic disease. This review provides an overview of how model organisms have contributed to our understanding of genetic disease, with a focus on the roles of yeast and zebrafish in gene discovery and the identification of compounds that could potentially treat human genetic diseases.