Indoor scenario has emerged as one of the most congested, contested, and competitive wireless environments. With the need of resilient Internet of Everything (IoE) and Fourth Industrial Revolution (Industry 4.0) infrastructures, we expect to connect thousands of devices within a confined indoor environment, interfering to each other and contending for limited electromagnetic spectrum. While the growing demand for data traffic meets confined space and congested spectrum, it creates a clear and present technical challenge, and opportunities for innovation. The research objective of this proposal is to investigate new fundamental communication models and schemes, which dynamically program and customize indoor wireless propagation environments for enhanced wireless communication. This objective is attained by integrating the physics of wave-chaotic dynamics, the mathematics of random matrix theory, the engineering of reconfigurable electromagnetic surfaces, and the computing power of adiabatic quantum annealer. The proposed work consists of three components: (1) rigorous mathematical model for the statistical analysis of wave physics in complex confined indoor environment; (2) the configuration and control of wave chaos using reconfigurable intelligent surfaces; (3) Quantum-enabled, ultra-fast large-scale optimization of reconfigurable intelligent surface configuration.

In most plants, growth rate is limited by the rate at which carbon dioxide from the atmosphere is taken up and converted to sugars in the process of photosynthesis. The enzyme responsible for the first step in this process, Rubisco, does not work at its potential maximum efficiency at the current levels of carbon dioxide present in the atmosphere. If levels were much higher, photosynthesis would be increased and plant productivity would be higher. There is an immediate requirement for increased crop productivity to provide food for the rising population of the planet. Our project addresses this problem. We are studying a mechanism present in unicellular green algae that results in high concentrations of carbon dioxide inside their photosynthesising cells (called a Carbon Concentrating Mechanism, or CCM), enabling Rubisco to work at maximum efficiency. During the initial CAPP1 programme, we discovered important new information about this mechanism, and using new and rapid methods we have identified novel algal genes and additional regulatory components which allow the CCM to operate in association with a specific micro-compartment called a pyrenoid. We have also successfully introduced some of these components into a model higher plant, Arabidopsis, and also successfully introduced a modified form of Rubisco which may facilitate aggregation into the pyrenoid. The ambitious goals of the CAPP2 extension will be to combine the expression of the CCM and pyrenoid in the Advanced Plant. Firstly, we will continue to identify genes required by the algae to achieve high concentrations of carbon dioxide inside the cells, and develop new markers and sensors to reveal the location and activity of these genes when expressed in the higher plant. Secondly, we will identify additional regulatory elements needed to form a pyrenoid, as well as exploring the impact on Rubisco enzyme efficiency and light utilisation. Thirdly, we will continue to introduce successive components into our model Advanced Plant so as to "stack" up the activities of CCM components and examine the extent of pyrenoid formation and enhanced productivity associated with the CCM. This work will provide new insights into how plants and algae acquire and use carbon dioxide from the atmosphere, of great importance in predicting and coping with the current rapid changes in the atmosphere and hence in climate. The work will also contribute to strategies to increase global food security, because it will indicate new ways in which crop productivity can be increased.

In 1980, Farquhar et al. (Planta 149, 78-90) published a mechanistic photosynthesis model that successfully predicted rates of net carbon dioxide exchange in C3 plants. The impact of that model on carbon exchange research has been profound, with their 1980 paper having been cited over 1300 times since publication. Why was the paper so influential? One reason was the ability of the model to help researchers understand the underlying factors controlling rates of net photosynthesis. The other was that because of its simplicity, it could be readily incorporated into large scale applications (e.g. canopy photosynthesis and climate models). But having successfully modeled photosynthesis, most large scale models then dispense with about half of the assimilate in respiration without attempting to more accurately predict variations in respiratory flux. This failure to correctly model plant respiration has important consequences for the accuracy of large scale models, as plant respiration releases ten times more carbon dioxide (one of the greenhouse gases responsible for global warming) than does the burning of fossil fuels etc. Clearly, it is time that a mechanistic 'Farquhar-like' model of plant respiration be constructed. In this research project, we will use oxygen titration curves of plant respiration to construct a plant respiration-equivalent of the Farquhar et al. model. In collaboration with colleagues at the University of Illinois in the USA, we will use a state-of-the-art oxygen analyser (currently not available in the UK) to measure rates of leaf respiration over a broad range of oxygen concentrations. This data will then be used to test the effectiveness of a mathematical model that takes into account factors such as enzyme activity and the ability of individual enzymes to consume oxygen. In addition to being of high predictive value, such a model would also enable us to better understand what underlying factors regulate variations in respiratory flux, particularly in leaves exposed to two key environmental parameters associated with climate change: temperature and atmospheric carbon dioxide concentration. Having developed the model under moderate temperature conditions at current concentrations of atmospheric carbon dioxide, we will then subject leaves to high and low temperatures and assess the impact of the temperature treatments on the model parameters. Then, the model will be used to better understand why rates of leaf respiration often increase in leaves exposed to elevated atmospheric carbon dioxide. We will use soybean (Glycine max) for our experiments, as much is known about the regulation of respiration in this species and how photosynthetic and respiratory metabolism respond to elevated atmospheric carbon dioxide concentrations. Given that the University of Illinois will cover most plant growth/consumable costs, the proposal represents excellent value for money for NERC and an opportunity to achieve an outcome that is not possible within the UK.

A large amount of money goes into funding education, especially literacy, with the belief that there will be long-term, positive effects. However, literacy rates - especially in Sub-Saharan Africa - remain incredibly low. Very few of the hundreds of rigorously evaluated interventions show more than moderate gains in student learning; almost none provide longitudinal evidence on longer-term outcomes. In short, there is little evidence from longitudinal studies in Africa about the effects of early learning on later school or life outcomes, and whether a strong early foundation better supports transitions, paving the way for continuing education, life-long learning and post-primary success. In response to this gap, our project will provide some of the first rigorous evidence regarding how investments in the early years of schooling from a highly successful literacy program can translate into long-term academic success and life outcomes. The project builds upon a randomized evaluation of an early grade literacy program in Northern Uganda. The evaluation involved 128 schools and studied a teacher training and support program for mother-tongue literacy in grades one through three. After four years of the program, we found massive effects of the program: Grade 4 pupils tested in 2017 after being exposed to the program in grades 1-3 scored 0.92 standard deviations higher in mother tongue reading - equivalent to 6.3 grade levels - more than the control students. The effects on English oral reading fluency were almost just as large. While it was impressive that such large gains were possible, in a post-conflict low-resource setting, a new set of open questions emerged. Specifically, at the end of 2017, only 52% of our study respondents were found during school visits. Importantly, we found no differential attrition across study arms - in other words, despite the unprecedented learning gains from the program, there was no positive impact on keeping children in school suggesting that outside factors - such as barriers and marginalization - rather than learning, play an important role in education transitions. This study addresses the following new questions: 1. How do children and parents/guardians plan for, and navigate challenges to, successful school and life transitions and how does early grade literacy help this navigation and transitions? 2. What are the causal effects of solid foundations in early grade literacy on learning, life skills, and school and life transitions? 3. What are the factors that, in a resource-poor environment, affect children's ability to harness the potential returns of early literacy skills? This proposed study will extend the NULP longitudinal data by interviewing a sub-sample of children and their parents/caregivers as they transition into adolescence. We will collect three rounds of data from children, and one round of data from parents/caregivers, over two years to measure learning life skills, school and life transitions. The study will conduct innovative qualitative child journey mapping and quantitative experimental analyses to provide some of the first evidence on how investments in the early years from a highly successful literacy program can improve learning, school and life transitions.

High diversity is a striking feature of almost all tropical forests, which provide numerous important ecosystem functions, and contribute to the resilience of communities in response to global change. Although several mechanisms have been proposed to explain the origin and maintenance of tropical forest diversity, recent theoretical work suggest that resource partitioning for soil phosphorus (P) is likely to be one of the main contributors to tropical plant diversity and coexistence. However, we currently lack vital experimental evidence to test this hypothesis, which requires understanding the relationships among mycorrhizal plant and fungal diversity, and soil P fractions in these systems, and how these associations relate to P utilisation. In this proposal, we will therefore determine the network of interactions among plants and mycorrhizal fungi in the field, and show using manipulation experiments whether this is related to edaphic factors, and in particular the composition and structure of the soil P pool. This aim requires coupling a comprehensive and unique dataset of spatial analyses of plant diversity with new analyses of mycorrhizal fungal diversity and soil nutrient pools in pristine tropical forest, and novel manipulation experiments. This project will show whether, despite overall nutrient limitation, the diversity of a mineral fraction in the soil is a driver of plant hyperdiversity. This will make a step-change in our understanding of the role of soil biodiversity in niche separation. The project will provide mechanistic insight into the maintenance of hyper-diverse plant communities and make a step-change in our understanding of the role of soil biodiversity in niche separation within tropical tree communities. It targets NERC priority areas in biodiversity, and will aid stakeholders who are charged with managing plant and soil biodiversity and the goods and services provided by tropical ecosystems (see Pathways to Impact).