Mother-infant interactions and regional brain volumes in infancy: an MRI study

Background: It is generally agreed that the human brain is responsive to environmental influences, and that the male brain may be particularly sensitive to early adversity. However, this is largely based on retrospective studies of older children and adolescents exposed to extreme environments in childhood. Less is understood about how normative variations in parent-child interactions are associated with the development of the infant brain in typical settings. Method: To address this, we used magnetic resonance imaging to investigate the relationship between observational measures of mother-infant interactions and regional brain volumes in a community sample of 3-6 month old infants (N=39). In addition, we examined whether this relationship differed in male and female infants. Results: We found that lower maternal sensitivity was correlated with smaller subcortical grey matter volumes in the whole sample, and that this was similar in both sexes. However, male infants who showed greater levels of positive communication and engagement during early interactions had smaller cerebellar volumes. Conclusion These preliminary findings suggest that variations in mother-infant interaction dimensions are associated with differences in infant brain development. Although the study is cross-sectional and causation cannot be inferred, the findings reveal a dynamic interaction between brain and environment that may be important when considering interventions to optimize infant outcomes

Challenges towards renewable energy : an exploratory study from the Arabian Gulf region

Considering the importance of energy for social and economic development, access to clean, affordable and reliable energy has been adopted as one of the United Nations sustainable development goals that all countries aim to achieve by 2030. However, much of the world's energy is still produced from fossil fuels and thus the progress towards clean and renewable energy is slow. This paper explores the key challenges towards renewable energy in Gulf Cooperation Council countries blessed with plenty of oil and gas reserves. The key challenges identified through literature review were ranked using a quantitative approach through the data collected from a selective sample across the six countries. These challenges in order of importance were found to be policies and regulations, manpower experience and competencies, renewable energy education, public awareness, costs and incentives for renewable energy and government commitment. The findings could be helpful to decision makers and government organisations in the region to develop strategies to overcome these identified challenges

Clustering individual transactional data for masses of users

Mining a large number of datasets recording human activities for making sense of individual data is the key enabler of a new wave of personalized knowledge-based services. In this paper we focus on the problem of clustering individual transactional data for a large mass of users. Transactional data is a very pervasive kind of information that is collected by several services, often involving huge pools of users. We propose txmeans, a parameter-free clustering algorithm able to efficiently partitioning transactional data in a completely automatic way. Txmeans is designed for the case where clustering must be applied on a massive number of different datasets, for instance when a large set of users need to be analyzed individually and each of them has generated a long history of transactions. A deep experimentation on both real and synthetic datasets shows the practical effectiveness of txmeans for the mass clustering of different personal datasets, and suggests that txmeans outperforms existing methods in terms of quality and efficiency. Finally, we present a personal cart assistant application based on txmeans