Ionic Influences on Recombination in Perovskite Solar Cells

The origins of recombination processes, particularly those that relate to IV hysteresis, are still unclear in perovskite solar cells. Of particular interest, is the impact different contact materials have on the level of hysteresis observed. This work shows that there is a clear link between ionic movement and interfacial recombination, which have both been shown to be responsible for hysteresis. By performing low temperature transient photovoltage (TPV) measurements over a period in which ions redistribute within the perovskite layer, the dominant recombination mechanism, responsible for hysteresis and other slow dynamic processes, is found to occur at the TiO2/perovskite interface. We observe an anomalous negative transient upon firing the laser pulse which we attribute to interfacial recombination at the TiO2/perovskite interface. The impact of recombination at the perovskite/HTL interface is shown to be negligible by performing TPV measurements using different laser wavelengths to probe different depths into the perovskite layer, as well as by changing the type of HTL used

The Family Nurse Partnership to reduce maltreatment and improve child health and development in young children: the BB:2–6 routine data-linkage follow-up to earlier RCT

BackgroundThe short-term effectiveness (to 24 months post partum) of a preventative home-visiting intervention, the Family Nurse Partnership, was previously assessed in the Building Blocks trial (BB:0–2).ObjectivesThe objectives were to establish the medium-term effectiveness of the Family Nurse Partnership in reducing maltreatment and improving maternal health (second pregnancies) and child health, developmental and educational outcomes (e.g. early educational attendance, school readiness); to explore effect moderators and mediators; and to describe the costs of enhancing usually provided health and social care with the Family Nurse Partnership.DesignChildren and their mothers from an existing trial cohort were followed up using routine data until the child was 7 years of age.SettingThis study was set in 18 partnerships between local authorities and health-care organisations in England.ParticipantsThe participants were mothers [and their firstborn child(ren)] recruited as pregnant women aged ≤ 19 years, in local authority Family Nurse Partnership catchment areas, at < 25 weeks’ gestation, able to provide consent and able to converse in English. Participants mandatorily withdrawn (e.g. owing to miscarriage) from the BB:0–2 trial were excluded.InterventionsThe intervention comprised up to a maximum of 64 home visits by specially trained family nurses from early pregnancy until the firstborn child was 2 years of age, plus usually provided health and social care support. The comparator was usual care alone.Main outcome measuresThe primary outcome measure was child-in-need status recorded at any time during follow-up. The secondary outcomes were as follows: (1) referral to social services, child protection registration (plan), child-in-need categorisation, looked-after status, recorded injuries and ingestions at any time during follow-up; (2) early child care and educational attendance, school readiness (Early Years Foundation Stage Profile score) and attainment at Key Stage 1; and (3) health-care costs.Data sourcesThe following data sources were used: maternally reported baseline and follow-up data (BB:0–2), Hospital Episode Statistics data (NHS Digital), social care and educational data (National Pupil Database) and abortions data (Department of Health and Social Care).ResultsThere were no differences between study arms in the rates of referral to social services, being registered as a child in need, receiving child protection plans, entering care or timing of first referral for children subsequently assessed as in need. There were no differences between study arms in rates of hospital emergency attendance, admission for injuries or ingestions, or in duration of stay for admitted children. Children in the Family Nurse Partnership arm were more likely to achieve a good level of development at reception age (school readiness), an effect strengthened when adjusting for birth month. Differences at Key Stage 1 were not statistically different, but, after adjusting for birth month, children in the Family Nurse Partnership arm were more likely to reach the expected standard in reading. Programme effects were greater for boys (Key Stage 1: writing); children of younger mothers (Key Stage 1: writing, Key Stage 1: mathematics); and children of mothers not in employment, education or training at study baseline (Key Stage 1: writing). There were no differences between families who were part of the Family Nurse Partnership and those who were not for any other outcome. The differences between study arms in resource use and costs were negligible.LimitationsThe outcomes are constrained to those available from routine sources.ConclusionsThere is no observable benefit of the programme for maltreatment or maternal outcomes, but it does generate advantages in school readiness and attainment at Key Stage 1

The Good Behaviour Game intervention to improve behavioural and other outcomes for children aged 7–8 years: a cluster RCT

BackgroundUniversal, school-based behaviour management interventions can produce meaningful improvements in children’s behaviour and other outcomes. However, the UK evidence base for these remains limited.ObjectiveThe objective of this trial was to investigate the impact, value for money and longer-term outcomes of the Good Behaviour Game. Study hypotheses centred on immediate impact (hypothesis 1); subgroup effects (at-risk boys, hypothesis 2); implementation effects (dosage, hypothesis 3); maintenance/sleeper effects (12- and 24-month post-intervention follow-ups, hypothesis 4); the temporal association between mental health and academic attainment (hypothesis 5); and the health economic impact of the Good Behaviour Game (hypothesis 6).DesignThis was a two-group, parallel, cluster-randomised controlled trial. Primary schools (n = 77) were randomly assigned to implement the Good Behaviour Game for 2 years or continue their usual practice, after which there was a 2-year follow-up period.SettingThe trial was set in primary schools across 23 local authorities in England.ParticipantsParticipants were children (n = 3084) aged 7–8 years attending participating schools.InterventionThe Good Behaviour Game is a universal behaviour management intervention. Its core components are classroom rules, team membership, monitoring behaviour and positive reinforcement. It is played alongside a normal classroom activity for a set time, during which children work in teams to win the game to access the agreed rewards. The Good Behaviour Game is a manualised intervention delivered by teachers who receive initial training and ongoing coaching.Main outcome measuresThe measures were conduct problems (primary outcome; teacher-rated Strengths and Difficulties Questionnaire scores); emotional symptoms (teacher-rated Strengths and Difficulties Questionnaire scores); psychological well-being, peer and social support, bullying (i.e. social acceptance) and school environment (self-report Kidscreen survey results); and school absence and exclusion from school (measured using National Pupil Database records). Measures of academic attainment (reading, standardised tests), disruptive behaviour, concentration problems and prosocial behaviour (Teacher Observation of Child Adaptation Checklist scores) were also collected during the 2-year follow-up period.ResultsThere was no evidence that the Good Behaviour Game improved any outcomes (hypothesis 1). The only significant subgroup moderator effect identified was contrary to expectations: at-risk boys in Good Behaviour Game schools reported higher rates of bullying (hypothesis 2). The moderating effect of the amount of time spent playing the Good Behaviour Game was unclear; in the context of both moderate (≥ 1030 minutes over 2 years) and high (≥ 1348 minutes over 2 years) intervention compliance, there were significant reductions in children’s psychological well-being, but also significant reductions in their school absence (hypothesis 3). The only medium-term intervention effect was for peer and social support at 24 months, but this was in a negative direction (hypothesis 4). After disaggregating within- and between-individual effects, we found no temporal within-individual associations between children’s mental health and their academic attainment (hypothesis 5). Last, our cost–consequences analysis indicated that the Good Behaviour Game does not provide value for money (hypothesis 6).LimitationsLimitations included the post-test-only design for several secondary outcomes; suboptimal implementation dosage (mitigated by complier-average causal effect estimation); and moderate child-level attrition (18.5% for the primary outcome analysis), particularly in the post-trial follow-up period (mitigated by the use of full information maximum likelihood procedures).Future workQuestions remain regarding programme differentiation (e.g. how distinct is the Good Behaviour Game from existing behaviour management practices, and does this makes a difference in terms of its impact?) and if the Good Behaviour Game is impactful when combined with a complementary preventative intervention (as has been the case in several earlier trials).ConclusionThe Good Behaviour Game cannot be recommended based on the findings reported here

Social Work Interventions in Cancer Care: Final Report

This report presents the findings of an intervention study investigating the reasons for referral to oncology social workers and the types of interventions undertaken by them. The study was an academic and practitioner collaboration between the University of Sydney and practitioners from six cancer care settings in metropolitan, regional and rural centres in New South Wales, Victoria and Queensland. Clinical data mining methodology was used, with a cross analysis of key variables mapped to existing social work classification systems. The findings indicated that high-level relationship-based skills were required to deliver social work services. Key domains of social work practice were linked to health inequalities. Areas for further research were identified including greater engagement with Aboriginal and Torres Strait Islander patients, the need for improved health literacy about the role of social work in their cancer treatment and the need for increased access to social workers and cancer services in rural and regional centres. This preprint is related to a published article: Rosalie Pockett, Kim Hobbs, Raymond Araullo & Kashmira Dave (2020) Social Work Interventions in Cancer Care, Australian Social Work, DOI: 10.1080/0312407X.2020.174867

Simultaneous Energy Harvesting and Hand Gesture Recognition in Large Area Monolithic Dye-Sensitized Solar Cells

Internet of Things (IoT) devices have become prevalent, embedding intelligence into our environment. It is projected that over 75 billion IoT devices will be connected by 2025 worldwide, with the majority being operated indoors. Dye-sensitized solar cells (DSSC) have recently been optimized for ambient light, having the capabilities of providing sufficient energy for self-powered IoT devices. Interaction with digital technologies, termed Human Computer Interaction (HCI), is often achieved via physical mechanisms (e.g. remote controls, cell phones) which can hinder the natural interface between users and IoT devices, a key consideration for HCI. What if the solar cell that is powering the IoT device can also recognize hand gestures which would allow the user to naturally interact with the system? Previous attempts to achieve this have necessarily employed an array of solar cell/photodiodes to detect directionality. In this work, we demonstrate that by monitoring the photocurrent output of an asymmetrically patterned monolithic (i.e., single cell) DSSC, and using machine learning, we can recognize simple hand gestures, achieving an accuracy prediction of 97.71%. This work shows that, DSSCs are the perfect choice for self-powered interactive technologies, both in terms of powering IoT devices in ambient light conditions and having aesthetic qualities that are prioritized by users. As well as powering interactive technologies, they can also provide a means of interactive control.Comment: Main body: 10 pages, 6 figures, 3 tables. Document includes supplementary info: 30 pages, 47 supplementary figure