Evaluating the immediate and longer term impact of a refusal conversion strategy in a large scale longitudinal study

Refusal conversion is one of the fieldwork strategies commonly used to minimise non-response in surveys. There is, however, relatively little evidence about the effectiveness of this strategy, particularly for face-to-face longitudinal surveys. Moreover, much of the existing evidence is based on observational studies. This paper evaluates the effectiveness of a fieldwork strategy – intensive re-issuing - to convert refusals using evidence from an intervention on a random sub-sample of refusals implemented in wave four of a large scale longitudinal study in the UK: the Millennium Cohort Study. We show that intensive re-issuing is an effective way of reducing the refusal rate. We also show that refusal conversion led to a modest reduction in non-response bias in the survey estimates for several key variables. The longer term impact of refusal conversion is also a key concern in longitudinal surveys. We demonstrate that, although the majority of converted refusals go on to participate in the subsequent wave of the study, there is no overall effect of intensive re-issuing on sample size at this wave

Extracellular heat shock proteins in cell signaling

AbstractExtracellular stress proteins including heat shock proteins (Hsp) and glucose regulated proteins (Grp) are emerging as important mediators of intercellular signaling and transport. Release of such proteins from cells is triggered by physical trauma and behavioral stress as well as exposure to immunological “danger signals”. Stress protein release occurs both through physiological secretion mechanisms and during cell death by necrosis. After release into the extracellular fluid, Hsp or Grp may then bind to the surfaces of adjacent cells and initiate signal transduction cascades as well as the transport of cargo molecules such as antigenic peptides. In addition Hsp60 and hsp70 are able to enter the bloodstream and may possess the ability to act at distant sites in the body. Many of the effects of extracellular stress proteins are mediated through cell surface receptors. Such receptors include Toll Like Receptors 2 and 4, CD40, CD91, CCR5 and members of the scavenger receptor family such as LOX-1 and SREC-1. The possession of a wide range of receptors for the Hsp and Grp family permits binding to a diverse range of cells and the performance of complex multicellular functions particularly in immune cells and neurones

A causal inference and Bayesian optimisation framework for modelling multi-trait relationships—Proof-of-concept using Brassica napus seed yield under controlled conditions

The improvement of crop yield is a major breeding target and there is a long history of research that has focussed on unravelling the mechanisms and processes that contribute to yield. Quantitative prediction of the interplay between morphological traits, and the effects of these trait-trait relationships on seed production remains, however, a challenge. Consequently, the extent to which crop varieties optimise their morphology for a given environment is largely unknown. This work presents a new combination of existing methodologies by framing crop breeding as an optimisation problem and evaluates the extent to which existing varieties exhibit optimal morphologies under the test conditions. In this proof-of-concept study using spring and winter oilseed rape plants grown under greenhouse conditions, we employ causal inference to model the hierarchically structured effects of 27 morphological yield traits on each other. We perform Bayesian optimisation of seed yield, to identify and quantify the morphologies of ideotype plants, which are expected to be higher yielding than the varieties in the studied panels. Under the tested growth conditions, we find that existing spring varieties occupy the optimal regions of trait-space, but that potentially high yielding strategies are unexplored in extant winter varieties. The same approach can be used to evaluate trait (morphology) space for any environment

AI ethics: a framework for measuring embodied carbon in AI systems

This paper outlines the ethical implications of AI from a climate perspective. So far, much of the discussion around AI ethics have focused on bias, unexplainable outcomes, privacy and other social impacts of such systems. The role and contribution of AI towards climate change and the ethical implications of its contribution to an unjust distribution of impact on the planet, humans and flora and fauna have not yet been covered in detail within the technical community. Within this paper, we aim to raise some of the issues of AI associated with climate justice and we propose a framework that will allow the AI and ICT industries to measure their true impact on the planet, propose an organisational structure to take this work forward and propose future research areas for this important topic

Integrating Multiple Sources of Knowledge for the Intelligent Detection of Anomalous Sensory Data in a Mobile Robot

For service robots to expand in everyday scenarios they must be able to identify and manage abnormal situations intelligently. In this paper we work at a basic sensor level, by dealing with raw data produced by diverse devices subjected to some negative circumstances such as adverse environmental conditions or difficult to perceive objects. We have implemented a probabilistic Bayesian inference process for deducing whether the sensors are working nominally or not, which abnormal situation occurs, and even to correct their data. Our inference system works by integrating in a rigorous and homogeneous mathematical framework multiple sources and modalities of knowledge: human expert, external information systems, application-specific and temporal. The results on a real service robot navigating in a structured mixed indoor-outdoor environment demonstrate good detection capabilities and set a promising basis for improving robustness and safety in many common service tasks.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Views on social media and its linkage to longitudinal data from two generations of a UK cohort study

Background: Cohort studies gather huge volumes of information about a range of phenotypes but new sources of information such as social media data are yet to be integrated. Participant’s long-term engagement with cohort studies, as well as the potential for their social media data to be linked to other longitudinal data, could provide novel advances but may also give participants a unique perspective on the acceptability of this growing research area. Methods: Two focus groups explored participant views towards the acceptability and best practice for the collection of social media data for research purposes. Participants were drawn from the Avon Longitudinal Study of Parents and Children cohort; individuals from the index cohort of young people (N=9) and from the parent generation (N=5) took part in two separate 90-minute focus groups. The discussions were audio recorded and subjected to qualitative analysis. Results: Participants were generally supportive of the collection of social media data to facilitate health and social research. They felt that their trust in the cohort study would encourage them to do so. Concern was expressed about the collection of data from friends or connections who had not consented. In terms of best practice for collecting the data, participants generally preferred the use of anonymous data derived from social media to be shared with researchers. Conclusion: Cohort studies have trusting relationships with their participants; for this relationship to extend to linking their social media data with longitudinal information, procedural safeguards are needed. Participants understand the goals and potential of research integrating social media data into cohort studies, but further research is required on the acquisition of their friend’s data. The views gathered from participants provide important guidance for future work seeking to integrate social media in cohort studies