University of Southampton

Desertification caused by climate change and soil compaction caused by land use intensification are exacerbating social issues ranging from food security to civil development and are expected to worsen dramatically in the near future. Soil compaction from intensified farming affects 25-45% of Europe's arable land area. This results inincreased density, which makes soil's more rigid and harder to break. Similarly, as temperatures rise near the equator and droughts become more common, previously arable land will become deserts. As land becomes drier due to desertification, soils again become more brittle and rigid. This will have severe impacts on agriculture, which restrict soil penetration by growing plant roots and burrowing earthworms. These organisms are vital for crop and ecosystem health. As drier climates may pose a mechanical threat to food security, a better understanding of the fundamental factors that facilitate root growth becomes crucial. Few studies have investigated key physical constraints that shape below ground biological activity, the strategies these biological organisms employ in order to modify their own habitats, or the resulting impact that their modifications have on soil structural suitability. Understanding this biophysical interplay may harness greater potential to provide more sustainable farming and civil design practices. I propose to develop tools to assess the mechanical potential for soil to support biological activity that promotes agriculture under changing climates and land use practices. In order to move through soil, plant roots and earthworms must exert pressures that exceed the elastic limitations of soil to achieve deformations large enough for penetration. Under wetter conditions, inelastic soil deformation is ductile, and soil's resistance to penetration is lower. This facilitates biological movement below ground. However, as soil dries, capillarity pulls soil aggregates densely together and finer clay particles begin to bind tightly, which creates a more brittle and resistant body that hinders earthworm activity. Field compaction experiments have demonstrated that increased soil mechanical impedance also reduces crop yields. Despite the reduced efficacy of root growth under mechanically limiting conditions, studies have demonstrated that some plant roots still manage to exert pressures great enough to grow. A hypothesis for how roots achieve this is via multi-scale processes where root turgor pressure allows axial extension while cells near the tip multiply and reorient themselves acting to reduce local frictional effects and assemble past the root cap. While this ensemble of processes is suggested to allow some roots to locally exert up to 1 MPa of pressure (capable of fracturing chalk), there is no clear understanding as to how this growth mechanism can enable this magnitude of pressure nor at what scales these loads are actually being applied. Knowledge of these processes may unlock plant traits which can be harnessed to reclaim desertified land and maintain healthy soils in semi-arid regions. Besides being able to see below ground, X-ray techniques can also be used to determine physical forces acting on objects. To this end, I intend to couple X-ray techniques in order to measure and monitor below ground activity with mathematical models to interpret and quantify the forces they apply below ground. The results from my work will ultimately outline mechanical constraints that hinder biophysical activity as well as unveil key biophysical processes that facilitate plant growth under harsh climatic conditions. These considerations could be used to help remediate damaged land caused by climate change or land use intensification and better inform future agricultural practices.

According to the 2001 Census, persons from Black and Minority Ethnic (BME) groups comprised about 10% of the total UK population, and more recent analysis of the Understanding Society dataset shows that about 14% of the UK's define themselves as belonging to a minority ethnic group. Although the age structure of the BME population is relatively young and only 4% of the total UK population aged 50 and over belong to BME groups, projections show an increasing share of BME older people in an increasingly diverse and ageing UK population. Socio-economic and health differentials between the BME population and the White majority, and between different BME groups, have been well-evidenced in the literature and reflect a disadvantageous position across the life course and in later life. For example, Pakistani, Bangladeshi and Indian persons aged 50 and over are more likely to report a limiting long-standing illness than their White counterparts, while the Pakistani and Bangladeshi groups are more likely than any other ethnic minority group to be at the bottom quintile of the income distribution. In terms of employment, about one-third of Bangladeshi and Pakistani men aged 25-64 are unemployed, and the proportion among women in the equivalent ethnic and age group is more than 80%. Such differentials in employment patterns contribute to low pension coverage among BME groups, particularly in terms of occupational and private pension schemes which research has shown to make a difference in an individual's likelihood of experiencing a poverty risk in later life. This context raises important policy-relevant questions about the wellbeing of older people from BME groups, and about the prospects of pension protection among future cohorts of BME persons. Much of the previous literature in this area is from the 1990s and early 2000s. Over the past decade, there has been a new wave of migration from Eastern Europe that has added a further layer of complexity to the BME population. Estimates from ONS highlight that around 6% of the population aged 25-44 in England and Wales are defined as non-British 'White'. Moreover, many of those aged under 45 from the Asian and Black ethnic populations are 'second generation', having been born in the UK. Furthermore, changes in pensions policy over the past decade have transformed the pensions landscape, with a shift away from defined benefit towards defined contribution pensions and a greater emphasis on the individual life course. Thus it is timely to revisit this area. The proposed project aims to exploit two nationally-representative datasets (Understanding Society and Labour Force Survey) in order to study the prospects of pension adequacy among individuals from BME groups in early- and mid-life, as well as the current differentials in pension protection between older persons from different BME groups, and between the BME population and the White majority. The two datasets include sufficient cell counts in order to study the BME population in early (20-44), mid- (45-64) and later (65 and over) life, and a range of variables which relate to the individuals' economic (eg. employer pension membership) and social (eg. living arrangements) resources. In addition, the research will pay particular attention to gender differences in pension protection within and between BME groups, in order to better understand the impact of informal care provision on pension income in later life, and to draw policy-relevant lessons in this area. The proposed research addresses the aims of the ESRC's Secondary Data Analysis Initiative in three distinct ways: firstly, by maximising the value of existing data resources; secondly, by developing high-quality evidence which can inform the future design of policy in the area of pension protection for BME groups and contribute to the effectiveness of social policy in this field; and thirdly, by engaging key stakeholders in the area of the wellbeing of BME older persons.

Humans as a social species are dependent on social interactions for survival (Sedikides, Skowronski and Dunbar, 2006). To regulate appropriate behaviours in the social world, we need knowledge about ourselves and how others respond to us (Heatherton et al., 2007). Research on the self has been central in the field of psychology for more than a century (e.g., James, 1890). Although behavioural studies provide a fundamental understanding of the self, how the self is represented in the brain remains unclear. The proposed study will rigorously examine how the self is represented in the brain, by using fMRI and MVPA. The self is a complex concept, which consists of various aspects and is related to many different psychological processes. Therefore, sensitively measuring the patterns of activation rather than solely knowing which regions are active, is important to increase the understanding of the self. Participants will firstly take part in a behavioural session where they will judge whether various words describe them or not. Next, each participant will perform two tasks whilst in the fMRI scanner: a word judgement task and an attention task. They will be presented with two different types of stimuli: trait adjectives (e.g., trustworthy, lazy, etc.) and social categories (e.g., students, British, etc.). The aim of the study is to examine whether the self is special and uniquely represented in the brain. If it is special, the self condition should evoke similar activation patterns regardless of task and stimuli, which can be identified by MVPA. We will recruit thirty neurologically healthy, right-handed adult participants with normal or corrected-to-normal vision. The sample size is based on previous studies (Kelley et al., 2002; Krishnan et al., 2016) Behavioural task Before the fMRI scan, participants will complete a behavioural task where they will judge whether social category words and trait adjectives describe themselves or not. This is to distinguish between self-relevant, and not relevant stimuli for the word judgement task (which they will perform during the fMRI session). fMRI tasks Participants will perform the following tasks whilst in the fMRI scanner: 1. Word judgement task: Participants will be presented with words that are either a trait adjective or a social category word. Their task will be to judge whether the words presented describes themselves or not. 2. Attention task: Participants will again be presented with the same trait adjectives or social category words. Their task will be to judge whether the word is written in italic or not. For both tasks, the participants will indicate their answers by pressing one of two buttons on a response box in the scanner. Analyses and Hypotheses: We will firstly compare regions of neural activation for when participants are presented with self-relevant stimuli to when they are not, in both tasks. Secondly, we will examine whether self-relevant stimuli and other stimuli evoke similar activation patterns or not using MVPA. We hypothesise that self-relevant stimuli in both tasks will activate the CMS (univariate analysis) and that self-relevant stimuli in both tasks will evoke similar activation patterns in the CMS, while the patterns will be distinct from those evoked by other non-self-relevant stimuli (MVPA). Understanding ourselves is crucial for many aspects of our lives, for example; social interactions, evaluating ourselves or regulating thoughts and behaviours to reach goals. Thus, it is important to understand the underlying neural and psychological processes of the self. Although the self has been thoroughly investigated for a long time, how the self is processed in the brain remains unknown. The aim is to close this gap in the literature by examining the representation of the self in the brain with MVPA. In this way, the proposed project crosses disciplinary boundaries by using tools from neuroscience and computer science.

The role of river flow is regulating ocean acidification in Belizean Coastal waters

The latest announcement from the Carbon Trust on Pyrolysis Challenge highlights the importance of pyrolysis-oil as the potential replacement for transport fuels with low system GHG (green house gases) emissions. The two main barriers are outlined in Pyrolysis Challenge : a) to develop fast pyrolysis process to produce a better quality oil at low cost and large scale; b) upgrading the oil preferably with existing refinery. Without the technology and capacity to provide pyrolysis oils in large quantity and low cost, the investment in developing bio-oil upgrading technology and refinery will not be forthcoming. Therefore the development of fast pyroloysis process suitable for scale-up is the most impending issue. This project will focus on the development of computational models which work as effective tools for process design, optimisation and scale-up for biomass fast pyrolysis systems. UK has the technology base to become the world leader in pyrolysis technology and South Africa has the potential to be a major pyrolysis oil manufacturer in the world. This proposal is to form a constructive collaboration with UK expertise in computational modelling and South Africa experience in chemical process engineering. The UK and SA institutes will act as hubs to integrate this project with on-going national research programmes to enable a much wider participation. The project is expected to have catalytic effects to stimulate more collaborative research and commercial exploitation between UK and South Africa.