Transgender Healthcare Teaching in the Undergraduate Medical School Curriculum

With increasing recognition of the diverse and specific needs of transgender individuals in a health care setting, lack of knowledge, poor attitudes and prejudice towards transgender patients can result in this population being afraid to access medical care. Educating medical students early in their career in a sensitive and inclusive manner could help change these attitudes. It has been shown that medical undergraduates and post-graduates often feel unprepared or uncomfortable in caring for transgender patients due to lack of training and experience2-4. The aim of this study was to address this through introduction of basic transgender healthcare education into the University of Glasgow undergraduate medical curriculum, with the goal of implementing further interactive and fully inclusive teaching

RNNs Implicitly Implement Tensor Product Representations

Recurrent neural networks (RNNs) can learn continuous vector representations of symbolic structures such as sequences and sentences; these representations often exhibit linear regularities (analogies). Such regularities motivate our hypothesis that RNNs that show such regularities implicitly compile symbolic structures into tensor product representations (TPRs; Smolensky, 1990), which additively combine tensor products of vectors representing roles (e.g., sequence positions) and vectors representing fillers (e.g., particular words). To test this hypothesis, we introduce Tensor Product Decomposition Networks (TPDNs), which use TPRs to approximate existing vector representations. We demonstrate using synthetic data that TPDNs can successfully approximate linear and tree-based RNN autoencoder representations, suggesting that these representations exhibit interpretable compositional structure; we explore the settings that lead RNNs to induce such structure-sensitive representations. By contrast, further TPDN experiments show that the representations of four models trained to encode naturally-occurring sentences can be largely approximated with a bag of words, with only marginal improvements from more sophisticated structures. We conclude that TPDNs provide a powerful method for interpreting vector representations, and that standard RNNs can induce compositional sequence representations that are remarkably well approximated by TPRs; at the same time, existing training tasks for sentence representation learning may not be sufficient for inducing robust structural representations.Comment: Accepted to ICLR 201

Influence of reheating on the trispectrum and its scale dependence

We study the evolution of the non-linear curvature perturbation during perturbative reheating, and hence how observables evolve to their final values which we may compare against observations. Our study includes the evolution of the two trispectrum parameters, \gnl and \taunl, as well as the scale dependence of both \fnl and \taunl. In general the evolution is significant and must be taken into account, which means that models of multifield inflation cannot be compared to observations without specifying how the subsequent reheating takes place. If the trispectrum is large at the end of inflation, it normally remains large at the end of reheating. In the classes of models we study, it is very hard to generate \taunl\gg\fnl^2, regardless of the decay rates of the fields. Similarly, for the classes of models in which \gnl\simeq\taunl during slow--roll inflation, we find the relation typically remains valid during reheating. Therefore it is possible to observationally test such classes of models without specifying the parameters of reheating, even though the individual observables are sensitive to the details of reheating. It is hard to generate an observably large \gnl however. The runnings, \nfnl and \ntaunl, tend to satisfy a consistency relation \ntaunl=(3/2)\nfnl, but are in general too small to be observed for the class of models considered regardless of reheating timescale

A real-time PCR method for quantification of the total and major variant strains of the Deformed wing virus

Funding: ELB was supported by a Biotechnology and Biological Sciences Research Council (BBSRC) EASTBIO Doctoral Training Partnership (http://www.bbsrc.ac.uk) [grant number BB/J01446X/1] and an Eastern Association Regional Studentship (EARS) and The Morley Agricultural Foundation awarded to ASB. CRC was supported by a KTN BBSRC CASE studentship (BB/M503526/1) (http://www.bbsrc.ac.uk), part-funded by the Scottish Beekeeping Association (https://www.scottishbeekeepers.org.uk/) and the Animal Health - Disease Prevention, Scottish Government awarded to ASB CRC. This project received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no 613960 (SMARTBEES) (http://www.smartbees-fp7.eu/) awarded to ASB. The funders had no role in study design, data collection and analysis decision to publish, or preparation of the manuscript. Acknowledgments The authors wish to thank Mr W. Thrale, Mr Z. Blackmore, Mr J. Quinlan, and Mr J. Palombo for sample collection from the South East of England and Margie Ramsey for Beinn Eighe National Nature Reserve sample collection.Peer reviewedPublisher PD

Non-invasive estimation of left atrial dominant frequency in atrial fibrillation from different electrode sites: Insight from body surface potential mapping

© 2014, CardioFront LLC. All rights reserved. The dominant driving sources of atrial fibrillation are often found in the left atrium, but the expression of left atrial activation on the body surface is poorly understood. Using body surface potential mapping and simultaneous invasive measurements of left atrial activation our aim was to describe the expression of the left atrial dominant fibrillation frequency across the body surface. 20 patients in atrial fibrillation were studied. The spatial distributions of the dominant atrial fibrillation frequency across anterior and posterior sites on the body surface were quantified. Their relationship with invasive left atrial dominant fibrillation frequency was assessed by linear regression analysis, and the coefficient of determination was calculated for each body surface site. The correlation between intracardiac and body surface dominant frequency was significantly higher with posterior compared with anterior sites (coefficient of determination 67±8% vs 48±2%,

Time-domain THz spectroscopy reveals coupled protein-hydration dielectric response in solutions of native and fibrils of human lyso-zyme

Here we reveal details of the interaction between human lysozyme proteins, both native and fibrils, and their water environment by intense terahertz time domain spectroscopy. With the aid of a rigorous dielectric model, we determine the amplitude and phase of the oscillating dipole induced by the THz field in the volume containing the protein and its hydration water. At low concentrations, the amplitude of this induced dipolar response decreases with increasing concentration. Beyond a certain threshold, marking the onset of the interactions between the extended hydration shells, the amplitude remains fixed but the phase of the induced dipolar response, which is initially in phase with the applied THz field, begins to change. The changes observed in the THz response reveal protein-protein interactions me-diated by extended hydration layers, which may control fibril formation and may have an important role in chemical recognition phenomena