Machine learning techniques for the prediction of indoor gamma-ray dose rates - Strengths, weaknesses and implications for epidemiology.

We investigate methods that improve the estimation of indoor gamma ray dose rates at locations where measurements had not been made. These new predictions use a greater range of modelling techniques and larger variety of explanatory variables than our previous examinations of this subject. Specifically, we now employ three types of machine learning models in addition to the geostatistical, nearest neighbour and other earlier models.

Impact of nurse education prior to and during COVID-19 on nursing students' preparedness for clinical placement: A qualitative study.

Introduction: Nursing students internationally entered challenging clinical placements during COVID-19. Lessons learnt could inform nurse education planning, particularly in preparation to implement future workforce plans.

Aim: This study aimed to explore the impact of COVID-19 on nursing students undertaking clinical placements across the UK, particularly the extent to which nursing education prior to and during COVID-19 had prepared them for placements, and to distil key messages for future nursing education.

Nutation Spectroscopy of a Weakly Interacting Heterobimetallic Spin System.

The use of V and Cu spins to design weakly coupled and dissymmetric spin systems has been examined. Such systems were synthesized using porphyrin-based complexes, with external coordination sites allowing for the formation of dimers via a Pd linker ion. Continuous-wave (CW) Electron Paramagnetic Resonance (EPR) spectroscopy allowed the unequivocal magnetic characterization of the mononuclear precursors VO and Cu.

Leveraging Trauma Informed Care for Digital Health Intervention Development in Opioid Use Disorder.

Digital health refers to the use of information and communication technologies in medicine (including smartphone apps, wearables, other non-invasive sensors, informatics and telehealth platforms) to prevent illness, deliver treatment, and promote wellness. This rapidly proliferating group of technologies has the potential to reduce harm for people with opioid use disorder (OUD) and facilitate the recovery process; however, development in this space for OUD has been slower compared to that for other medical conditions. Unique issues with OUD management surrounding patient provider relationships, interaction with the healthcare system, autonomy and trust sometimes hinder care approaches, including those in digital health.