No abstract

Promoting social cohesion through education has re-emerged as an important policy objective in many countries during the past decade. But there is little clarity in policy discussions about what social cohesion means and how education may affect it. In this article we distinguish between social capital and societal cohesion and argue that education acts in differential ways on each. Using comparative, cross-country analysis, we develop a 'distributional model' which shows the relationship between equality of educational outcomes and various measures of social cohesion. In the final part of the article we discuss theories explaining the cross-country trends and variations in educational inequality and social inheritance in education, and argue that education system characteristics, such as degrees of 'comprehensiveness' in secondary schooling, may be an important factor in both. We conclude by arguing that policies to increase social cohesion through education must pay more attention to the reduction of educational equality than they currently do.

Severe space weather was identified as a risk to the UK in 2010 as part of a wider review of natural hazards triggered by the societal disruption caused by the eruption of the Eyjafjallajökull volcano in April of that year. To support further risk assessment by government officials, and at their request, we developed a set of reasonable worst‐case scenarios and first published them as a technical report in 2012 (current version published in 2020). Each scenario focused on a space weather environment that could disrupt a particular national infrastructure such as electric power or satellites, thus, enabling officials to explore the resilience of that infrastructure against severe space weather through discussions with relevant experts from other parts of government and with the operators of that infrastructure. This approach also encouraged us to focus on the environmental features that are key to generating adverse impacts. In this paper, we outline the scientific evidence that we have used to develop these scenarios, and the refinements made to them as new evidence emerged. We show how these scenarios are also considered as an ensemble so that government officials can prepare for a severe space weather event, during which many or all of the different scenarios will materialize. Finally, we note that this ensemble also needs to include insights into how public behavior will play out during a severe space weather event and hence the importance of providing robust, evidence‐based information on space weather and its adverse impacts.

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Natural disasters are frequently exacerbated by anthropogenic mechanisms and have social and political consequences for communities. The role of community learning in disasters is seen to be increasingly important. However, the ways in which such learning unfolds in a disaster can differ substantially from case to case. This article uses a comparative case study methodology to examine catastrophes and major disasters from five countries (Japan, New Zealand, the UK, the USA and Germany) to consider how community learning and adaptation occurs. An ecological model of learning is considered, where community learning is of small loop (adaptive, incremental, experimental) type or large loop (paradigm changing) type. Using this model, we consider that there are three types of community learning that occur in disasters (navigation, organization, reframing). The type of community learning that actually develops in a disaster depends upon a range of social factors such as stress and trauma, civic innovation and coercion.

Ion-mobiiity spectra can exhibit significant variations of mobiilty with temperature due to ion/moiecuie reactions occurring in the drift region. I n this paper the observed mobility for reactions in equilibrium has been shown to be calculable from the mobilities of the reacting species and the enthalpy change of the reaction. Several examples are included.

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Artificial minielastin constructs have been designed that replicate the structure and function of natural elastins in a simpler context, allowing the NMR observation of structure and dynamics of elastin-like proteins with complete residue-specific resolution. We find that the alanine-rich cross-linking domains of elastin have a partially helical structure, but only when capped by proline-rich hydrophobic domains. We also find that the hydrophobic domains, composed of prominent 6-residue repeats VPGVGG and APGVGV found in natural elastins, appear random coil by both NMR chemical shift analysis and circular dichroism. However, these elastin hydrophobic domains exhibit structural bias for a dynamically disordered conformation that is neither helical nor β sheet with a degree of nonrandom structural bias which is dependent on residue type and position in the sequence. Another nonrandom-coil aspect of hydrophobic domain structure lies in the fact that, in contrast to other intrinsically disordered proteins, these hydrophobic domains retain a relatively condensed conformation whether attached to cross-linking domains or not. Importantly, these domains and the proteins containing them constrict with increasing temperature by up to 30% in volume without becoming more ordered. This property is often observed in nonbiological polymers and suggests that temperature-driven constriction is a new type of protein structural change that is linked to elastin's biological functions of coacervation-driven assembly and elastic recoil.