The Augmented Library: Motivating STEM Students

Review of first-year Computing and Gaming Technology students undertaking Personal Development Planning as part of a key year one module showed a lack of engagement (and submission of work). Research shows STEM students traditionally spend little time in formal library settings, and thus lack knowledge of the process of research. This work is focused on encouraging students’ transition from their online ‘persona’ in multiple contexts to ‘becoming’ a student. Taking a radically different approach to the sessions, the students, in small groups, were tasked with cocreating library artefacts through the medium of Augmented Reality. Weekly classes were ‘flipped’ and used for feedback, discussion, and exposure to research in action, where they became part of, and embodied within the research process. Our findings show significant and enhanced engagement with the learning process, and higher coursework submission rates

Neurokinin 3 receptor antagonists compared with serotonin norepinephrine reuptake inhibitors for non-hormonal treatment of menopausal hot flushes : a systematic qualitative review

Hot flushes/flashes (HFs) or other vasomotor symptoms affect between 45 and 97% of women during menopause. Hormone replacement therapy (HRT) is effective at alleviating menopausal symptoms, but some women cannot or prefer not to take HRT. Since current non-hormonal options have suboptimal efficacy/tolerability, there is a pressing need for an effective, well-tolerated alternative. The neurokinin 3 receptor (NK3R) has recently been implicated in the generation of menopausal HFs and represents a novel therapeutic target to ameliorate HF symptoms. This review aims to assess if NK3R antagonists (NK3Ras) are more effective than Serotonin Norepinephrine Reuptake Inhibitors (SNRIs)—currently a common choice for non-hormonal treatment of menopausal HFs.Publisher PDFPeer reviewe

Investigating Temporal Features of Carotid Intima-Media Thickness from Ultrasound Imaging with Recurrent Neural Networks

Measuring carotid intima-media thickness (cIMT) of the Common Carotid Artery (CCA) via B-mode ultrasound imaging is a non-invasive yet effective way to monitor and assess cardiovascular risk. Recent studies using Convolutional Neural Networks (CNNs) to automate the process have mainly focused on the detection of regions of interest (ROI) in single frame images collected at fixed timepoints and have not exploited the temporal information captured in ultrasound imaging. This paper presents a novel framework to investigate the temporal features of cIMT, in which Recurrent Neural Networks (RNN) were deployed for ROI detection using consecutive frames from ultrasound imaging. The cIMT time series can be formed from estimates of cIMT in each frame of an ultrasound scan, from which additional information (such as min, max, mean, and frequency) on cIMT time series can be extracted. Results from evaluation show the best performance for ROI detection improved 4.75% by RNN compared to CNN-based methods. Furthermore, the heart rate estimated from the cIMT time series for seven patients was highly correlated with the patient’s clinical records, which suggests the potential application of the cIMT time series and related features for clinical studies in the future.<br/

The Evolution of the Hydrogen Thyratron

Abstract and Introduction