Radioactive metals disposal and recycling impact modelling

Screening life cycle assessment models developed to investigate hypothetical disposal and recycling options for the Windscale Advanced Gas-cooled Reactor heat exchangers were used to generate more complex models addressing the main UK radioactive metals inventory. Both studies show there are significant environmental advantages in the metals recycling promoted by the current low level waste disposal policies, strategies and plans. Financial benefits from current metals treatment options are supported and offer even greater benefits when applied to the UK radioactive metals inventory as a whole

Cystic fibrosis mice carrying the missense mutation G551D replicate human genotype phenotype correlations

We have generated a mouse carrying the human G551D mutation in the cystic fibrosis transmembrane conductance regulator gene (CFTR) by a one-step gene targeting procedure. These mutant mice show cystic fibrosis pathology but have a reduced risk of fatal intestinal blockage compared with 'null' mutants, in keeping with the reduced incidence of meconium ileus in G551D patients. The G551D mutant mice show greatly reduced CFTR-related chloride transport, displaying activity intermediate between that of cftr(mlUNC) replacement ('null') and cftr(mlHGU) insertional (residual activity) mutants and equivalent to approximately 4% of wild-type CFTR activity. The long-term survival of these animals should provide an excellent model with which to study cystic fibrosis, and they illustrate the value of mouse models carrying relevant mutations for examining genotype-phenotype correlations

The incidence and make up of ability grouped sets in the UK primary school

The adoption of setting in the primary school (pupils ability grouped across classes for particular subjects) emerged during the 1990s as a means to raise standards. Recent research based on 8875 children in the Millennium Cohort Study showed that 25.8% of children in Year 2 were set for literacy and mathematics and a further 11.2% of children were set for mathematics or literacy alone. Logistic regression analysis showed that the best predictors of being in the top set for literacy or mathematics were whether the child was born in the Autumn or Winter and cognitive ability scores. Boys were significantly more likely than girls to be in the bottom literacy set. Family circumstances held less importance for setting placement compared with the child’s own characteristics, although they were more important in relation to bottom set placement. Children in bottom sets were significantly more likely to be part of a long-term single parent household, have experienced poverty, and not to have a mother with qualifications at NVQ3 or higher levels. The findings are discussed in relation to earlier research and the implications for schools are set out

An Investigation into Gender Disparities in the Field of Computing

This paper explains the reasons as to why there is under-representation of females computer science. Recent research undertaken at a British University focused on gender imbalance amongst academic staff in the Faculty of Technology and Environment, Liverpool John Moores University. The paper presents evidence that suggests the significance of identifying female role models in the field as a precursor to improving the current gender imbalance amongst academic faculty. In addition, the paper suggests the importance of addressing the negative stereotypical images related to the discipline and suggests the importance of identifying barriers to access and mobility females encounter in the field. The results of this initial investigation demonstrate the subjective belief amongst female academic faculty that in the School of Computing is dominated by male academics. Further, this belief pattern manifests itself in a perceived lack of motivation for promotion in the School. It can be concluded that the deeply entrenched belief system determines a lack of attempts to seek and secure promotion amongst all grades of female faculty. The paper proposes recommendations which the School could adopt to improve recruitment and retention of female academic staff and students

A Data Science and Machine Learning Approach to Measure and Monitor Physical Activity in Children

Physical Activity is a fundamental component for the maintenance of a healthy lifestyle. Recommendations for physical activity levels are issued by most governments as part of public health measures. Therefore, it is vital for regulatory purposes, that there are reliable measurements of physical activity. However, the techniques and protocols used in existing physical activity research, including laboratory-based measurement, have received increasingly critical scrutiny in recent times. Consequently, physical activity researchers have begun to explore the use of wearable sensing technology to capture large amounts of data and the use of machine learning techniques, specifically artificial neural networks, to produce classifications for specific physical activity events. This paper explores this idea further and presents a supervised machine learning approach that utilises data obtained from accelerometer sensors worn by children in free-living environments. The paper posits a rigorous data science approach that presents a set of activities and features suitable for measuring physical activity in children in free-living environments. A Multilayer Perceptron neural network is used to classify physical activities by activity type, using ecologically valid data from body worn accelerometer sensors. A rigorous reproducible data science methodology is presented for subsequent use in physical activity research. Our results show that it was possible to obtain an overall accuracy of 92% using the initial data set, and 99.8% using interpolated cases

Secondary school pupils' preferences for different types of structured grouping practices

The aim of this paper is to explore pupils’ preferences for particular types of grouping practices an area neglected in earlier research focusing on the personal and social outcomes of ability grouping. The sample comprised over 5,000 year 9 pupils (aged 13-14 years) in 45 mixed secondary comprehensive schools in England. The schools represented three levels of ability grouping in the lower school (years 7 to 9). Pupils responded to a questionnaire which explored the types of grouping that they preferred and the reasons for their choices. The majority of pupils preferred setting, although this was mediated by their set placement, type of school, socio-economic status and gender. The key reason given for this preference was that it enabled work to be matched to learning needs. The paper considers whether there are other ways of achieving this avoiding the negative social and personal outcomes of setting for some pupils

Functional near infrared spectroscopy (fNIRS) to assess cognitive function in infants in rural Africa

Cortical mapping of cognitive function during infancy is poorly understood in low-income countries due to the lack of transportable neuroimaging methods. We have successfully piloted functional near infrared spectroscopy (fNIRS) as a neuroimaging tool in rural Gambia. Four-to-eight month old infants watched videos of Gambian adults perform social movements, while haemodynamic responses were recorded using fNIRS. We found distinct regions of the posterior superior temporal and inferior frontal cortex that evidenced either visual-social activation or vocally selective activation (vocal > non-vocal). The patterns of selective cortical activation in Gambian infants replicated those observed within similar aged infants in the UK. These are the first reported data on the measurement of localized functional brain activity in young infants in Africa and demonstrate the potential that fNIRS offers for field-based neuroimaging research of cognitive function in resource-poor rural communities

Functional near infrared spectroscopy (fNIRS) to assess cognitive function in infants in rural Africa

Cortical mapping of cognitive function during infancy is poorly understood in low-income countries due to the lack of transportable neuroimaging methods. We have successfully piloted functional near infrared spectroscopy (fNIRS) as a neuroimaging tool in rural Gambia. Four-to-eight month old infants watched videos of Gambian adults perform social movements, while haemodynamic responses were recorded using fNIRS. We found distinct regions of the posterior superior temporal and inferior frontal cortex that evidenced either visual-social activation or vocally selective activation (vocal > non-vocal). The patterns of selective cortical activation in Gambian infants replicated those observed within similar aged infants in the UK. These are the first reported data on the measurement of localized functional brain activity in young infants in Africa and demonstrate the potential that fNIRS offers for field-based neuroimaging research of cognitive function in resource-poor rural communities