• Canada
• 2021 close

The EcoScope project will develop an interoperable platform and a robust decision-making toolbox, available through a single public portal, to promote an efficient, ecosystem-based fisheries management. It will be guided by policy makers and scientific advisory bodies, and address ecosystem degradation and the anthropogenic impact that are causing fisheries to be unsustainably exploited across European Seas. The EcoScope Platform will organise and homogenise climatic, oceanographic, biogeochemical, biological and fisheries datasets for European Seas to a common standard type and format that will be available through interactive mapping layers. The EcoScope Toolbox, a scoring system based on assessments of all ecosystem components, ecosystem and economic models, will operate as a decision-support tool for examining fisheries management and marine policy scenarios and spatial planning simulations. Groups of end-users and stakeholders will be involved in the design, development and operation of both the platform and the toolbox. Novel assessment methods for data-poor fisheries, including non-commercial species, as well as for biodiversity and the conservation status of protected megafauna, will be used to assess the status of all ecosystem components across European Seas and test new technologies for evaluating the environmental, anthropogenic and climatic impact on ecosystems and fisheries. A series of sophisticated capacity building tools (online courses, webinars and games) will be available to stakeholders through the EcoScope Academy. The EcoScope project will provide an effective toolbox to decision makers and end-users that will be adaptive to their capacity, needs and data availability. The toolbox will incorporate methods for dealing with uncertainty; thus, it will promote efficient, holistic, sustainable, ecosystem-based fisheries management that will aid towards restoring fisheries sustainability and ensuring balance between food security and healthy seas.

The human mouth contains many different types of microorganisms that are often found attached to oral surfaces in 'sticky' communities called biofilms. These microorganisms are held in close proximity and will therefore likely influence the behaviour of each other. The effects of this could result in increased microbial growth, the displacement of some microorganisms to other sites, the alteration of gene expression and potentially, the enabling of microorganisms to cause infection. A PhD research project being done by Ms Megan Williams at the School of Dentistry, Cardiff University has been exploring how a fungus called Candida albicans can interact both with acrylic surfaces (used to manufacture dentures) and also with bacterial species often found alongside Candida albicans. To date, the work has indicated that colonisation of acrylic coated with different fluids, including those generated from tobacco smoking, may change the way Candida albicans grows. Candida albicans can grow as round cells called yeast, or as filamentous forms called hyphae. It is the hyphal forms that are often considered more damaging to human tissue surfaces during infection. In addition, the research shows that when certain bacteria are grown on acrylic surfaces with Candida albicans, hyphal development is also triggered. This is important, as it may mean that occurrence of infection by Candida albicans is at least in part determined by the community composition of the bacteria present alongside Candida. To date, the methods used to study these effects have included fluorescent microscopy, where the Candida is stained to fluoresce a different colour to bacteria and the surface of attachment. Whilst this approach allows quantification of attachment and imaging of the different growth forms, it cannot determine strength of cell-cell-surface interactions. Atomic Force Microscopy (AFM) is a method that provides images through measuring forces acting between a moving probe and a surface. It is possible to attach different molecules and even whole bacteria to the AFM probe, and in doing so, we can measure interactions occurring between bacteria, and either Candida yeast or hyphae serving as the substrate. Dr Laurent Bozec and his team at the University of Toronto are experts in use of AFM, which is not available in the School of dentistry, Cardiff. The exchange therefore offers the PhD student the opportunity to learn a new experimental technique, generate important data for the PhD and benefit from unique networking experiences. The results generated from this proposal will greatly enhance the research output and complement existing findings of the PhD. Ultimately, this could help determine how bacteria physically interact with Candida albicans and trigger the development of hyphal filaments to facilitate infection.

M-ERA.NET 3 aims at coordinating the research efforts in the participating EU Member States, Regions, and Associated States in materials research and innovation, including materials for future batteries, to support the circular economy and Sustainable Development Goals. A large network of national and regional funding organisations from 25 EU Members States, 4 Associated States and 6 countries outside Europe will implement a series of annual joint calls to fund excellent innovative transnational RTD cooperation, including one call for proposals with EU co-funding and additional non-cofunded calls. Continuing the activities started under the predecessor project M-ERA.NET 2 (3/2016-2/2021), the M-ERA.NET 3 consortium will address emerging technologies and related applications areas, such as - for example- surfaces, coatings, composites, additive manufacturing or integrated materials modelling. Research on materials supporting the large scale research initiative on future battery technologies will be particularly highlighted as a main target of the cofunded call (Call 2021) with a view to supporting in particular SDG 7 (“Affordable and clean energy”) by enabling electro mobility through sustainable energy storage technology and SDG 9 (“Industrial innovation and infrastructure”) by enhancing scientific research and upgrading the technological capabilities of industrial sectors. Several relevant action plans and initiatives will serve as programmatic guides for M-ERA.NET 3 when defining the joint activities, such as the Circular Economy Action Plan, the 2030 Agenda for Sustainable Development and its 17 Sustainable Development Goals, the EC communication “A clean planet for all”, and the “European Green Deal”. The total mobilised public call budget is expected to reach 150 million € with additional private investment of 50 million €. Thus, the leverage effect of the EU contribution will reach a factor of 13, exceeding by far the minimum required factor of 5.

The Circular Economy (CE) is a revolutionary alternative to a traditional linear, make-use-dispose economy. It is based on the central principle of maintaining continuous flows of resources at their highest value for the longest period and then recovering, cascading and regenerating products and materials at the end of each life cycle. Metals are ideal flows for a circular economy. With careful stewardship and good technology, metals mined from the Earth can be reused indefinitely. Technology metals (techmetals) are an essential, distinct, subset of specialist metals. Although they are used in much smaller quantities than industrial metals such as iron and aluminium, each techmetal has its own specific and special properties that give it essential functions in devices ranging from smart phones, batteries, wind turbines and solar cells to electric vehicles. Techmetals are thus essential enablers of a future circular, low carbon economy and demand for many is increasing rapidly. E.g., to meet the UK's 2050 ambition for offshore wind turbines will require 10 years' worth of global neodymium production. To replace all UK-based vehicles with electric vehicles would require 200% of cobalt and 75% of lithium currently produced globally each year. The UK is 100% reliant on imports of techmetals including from countries that represent geopolitical risks. Some techmetals are therefore called Critical Raw Materials (high economic importance and high risk of supply disruption). Only four of the 27 raw materials considered critical by the EU have an end-of-life recycling input rate higher than 10%. Our UKRI TechMet CE Centre brings together for the first time world-leading researchers to maximise opportunities around the provision of techmetals from primary and secondary sources, and lead materials stewardship, creating a National Techmetals Circular Economy Roadmap to accelerate us towards a circular economy. This will help the UK meet its Industrial Strategy Clean Growth agenda and its ambitious UK 2050 climate change targets with secure and environmentally-acceptable supplies of techmetals. There are many challenges to a future techmetal circular economy. With growing demand, new mining is needed and we must keep the environmental footprint of this primary production as low as possible. Materials stewardship of techmetals is difficult because their fate is often difficult to track. Most arrive in the UK 'hidden' in complex products from which they are difficult to recover. Collection is inefficient, consumers may not feel incentivised to recycle, and policy and legislative initiatives such as Extended Producer Responsibility focus on large volume metals rather than small quantity techmetals. There is a lack of end-to-end visibility and connection between different parts of techmetal value chains. The TechMet consortium brings together the Universities of Exeter, Birmingham, Leicester, Manchester and the British Geological Survey who are already working on how to improve the raw materials cycle, manufacture goods to be re-used and recycled, recycle complex goods such as batteries and use and re-use equipment for as long as possible before it needs recycling. One of our first tasks is to track the current flows of techmetals through the UK economy, which although fundamental, is poorly known. The Centre will conduct new interdisciplinary research on interventions to improve each stage in the cycle and join up the value chain - raw materials can be newly mined and recycled, and manufacturing technology can be linked directly to re-use and recycling. The environmental footprint of our techmetals will be evaluated. Business, regulatory and social experts will recommend how the UK can best put all these stages together to make a new techmetals circular economy and produce a strategy for its implementation.

ESRC : Emily MacLeod : ES/P000592/1. This exchange provides me with the opportunity to develop my existing expertise within science identities research, and make links within the field of teacher education and teaching identities research. There is a critical shortage of teachers globally; an ongoing issue which has far-reaching and negative consequences for schools and their students. The teacher shortage in the UK, where I am conducting my PhD and where I myself was a teacher, is particularly acute. Government teacher recruitment targets in England have been missed for the last seven years. However, this shortage is not evenly spread, and raises significant social justice concerns. For example, it has been estimated that schools in England would need an additional 68,000 Black and minority ethnic teachers for the workforce to reflect the population it teaches. Science especially faces some of the worst teacher shortages. But incentives to attract more people into science teaching have so far failed to make a significant impact on this shortage, and have tended to be financial; based upon the assumption that science graduates can earn considerably more outside of the relatively low-paid role of teaching. Unlike the well-documented shortage of teachers in England, there is currently very little research into the scale of the teacher shortage in Canada, partly due to differences in governance and contexts across the different provinces. However, in contrast to the surplus of teachers seen in recent years, there are now signs of an increasing shortage of teachers. This summer in Québec, where I intend to complete this exchange, the government reported that there were over 250 empty teacher vacancies in the province, and there are concerns that Covid-19 is likely to make things worse. As in England, there is also a severe and growing underrepresentation of people of colour in Canada's teaching workforce. This is particularly worrying within the context of an increasingly diverse Canadian population. Also as in England, this shortage is not spread evenly. Science teachers are some of the most needed. However, unlike in England, teacher salaries across Canada are amongst the highest of the OECD community, and subject-specific incentives have yet to be used. The shortage of science teachers especially, seen in both England and Canada, is of particular concern given that there is a globally-recognised STEM (Science, Technology, Engineering and Mathematics) skills shortage, likely to increase due to Covid-19. This growing demand for more young people studying and working in STEM will not be met without enough qualified science teachers. Yet in order to improve this situation, we need to better understand science teacher supply patterns. To date, research into teacher supply in science (and other disciplines) has been conducted by specialists in teacher education. From this we know that science teachers report becoming teachers not because they always wanted to, but after having had positive teaching-like experiences. We also know from existing science identities research from both the host and home supervisors that social and cultural influences work to influence whether and how people see different sciences roles as 'for me' or not. This exchange will help me to develop my research and communication skills whilst conducting comparative research to develop understandings of who does, and importantly who does not, want to become a science teacher in the UK and Canada, and why. I will build upon my existing expertise in science identity development amongst young people, and learn from the expertise of Dr Gonsalves and her colleagues in science teacher identities, and how teaching-like experiences can affect these identities. Combining these fields will help me to contribute to understandings of how people's identities shape how they feel about becoming science teachers.

Canada

Insects are the little things that run the world (E.O. Wilson). With increasing recognition of the importance of insects as the dominant component of almost all ecosystems, there are growing concerns that insect biodiversity has declined globally, with serious consequences for the ecosystem services on which we all depend. Major gaps in knowledge limit progress in understanding the magnitude and direction of change, and hamper the design of solutions. Information about insects trends is highly fragmented, and time-series data is restricted and unrepresentative, both between different groups of insects (e.g. lepidoptera vs beetles vs flies) and between different regions. Critically, we lack primary data from the most biodiverse parts of the world. For example, insects help sustain tropical ecosystems that play a major role in regulating the global climate system and the hydrological cycle that delivers drinking water to millions of people. To date, progress in insect monitoring has been hampered by many technical challenges. Insects are estimated to comprise around 80% of all described species, making it impossible to sample their populations in a consistent way across regions and ecosystems. Automated sensors, deep learning and computer vision offer the best practical and cost-effective solution for more standardised monitoring of insects across the globe. Inter-disciplinary research teams are needed to meet this challenge. Our project is timely to help UK researchers to develop new international partnerships and networks to underpin the development of long-term and sustainable collaborations for this exciting, yet nascent, research field that spans engineering, computing and biology. There is a pressing need for new research networks and partnerships to maximize potential to revolutionise the scope and capacity for insect monitoring worldwide. We will open up this research field through four main activities: (a) interactive, online and face-to-face engagement between academic and practitioner stakeholders, including key policy-makers, via online webinars and at focused knowledge exchange and grant-writing workshops in Canada and Europe; (b) a knowledge exchange mission between the UK and North America, to share practical experience of building and deploying sensors, develop deep learning and computer vision for insects, and to build data analysis pipelines to support research applications; (c) a proof-of-concept field trial spanning the UK, Denmark, The Netherlands, Canada, USA and Panama. Testing automated sensors against traditional approaches in a range of situation; (d) dissemination of shared learning throughout this project and wider initiatives, building a new community of practice with a shared vision for automated insect monitoring technology to meet its worldwide transformational potential. Together, these activities will make a significant contribution to the broader, long-term goal of delivering the urgent need for a practical solution to monitor insects anywhere in the world, to ultimately support a more comprehensive assessment of the patterns and consequences of insect declines, and impact of interventions. By building international partnerships and research networks we will develop sustainable collaborations to address how to quantify the complexities of insect dynamics and trends in response to multiple drivers, and evaluate the ecological and human-linked causes and consequences of the changes. Crucially, this project is a vital stepping-stone to help identify solutions for addressing the global biodiversity crisis as well as research to understand the biological impacts of climate change and to design solutions for sustainable agriculture. Effective insect monitoring underpins the evaluation of future socio-economic, land-use and climate mitigation policies.

AHRC : Alexander Hutterer : AH/R012709/1 Society and technology today face several information processing challenges. Human lives and digital technology become ever closer intertwined. Hence, we need to become better at understanding our own information processing practices. And we need to become more effective at using technology to aid and supplement our information processing activities. Philosophy plays a key role in explicating the meaning of the most fundamental concepts. Specifically, the sub-discipline of epistemology aims to help us understand what we mean when we say that we "believe," "know," or "understand" something. This can help us both with better understanding our contemporary socio-technological challenges and with finding solutions for them. For instance, one major challenge in the development of artificial intelligence is making it "understandable" to humans. This requires a clear picture of what it means for humans to understand something in the first place. Another example is the spreading of "fake news" via social media. Current solutions for this problem, like fact-checking, are insufficient. Part of the problem with this particular solution is that the implied aim is too ambitious, namely to "prove facts," a goal that even science does not necessarily reach. By better understanding these epistemic aims and practices, philosophy can help with the development of new, more effective solutions to challenges like the "post-truth" problem or AI development. The values and practices of today's science-powered society are frequently thought to stem from the enlightenment period. The enlightenment took place in the seventeenth and eighteenth centuries and coincided with significant improvements of human life, including the ascent of science and the beginnings of the industrial revolution. It was in the later stages of this period that Immanuel Kant wrote his ground-breaking "Critique of Pure Reason." In anglophone secondary literature on this book, Kant is usually understood as providing a new theory of how and what sort of "a priori knowledge," i.e., knowledge before experience, is attainable for humans. However, several recent papers in Kant scholarship cast doubt on this dominant interpretation. Instead, it is argued, Kant was not talking about knowledge at all. Specifically, he was talking about the German term "Erkenntnis" rather than knowledge. There is no clear translation for the term "Erkenntnis." The goal of my PhD is partly to figure out what precisely Kant meant by "Erkenntnis." If "Erkenntnis" really differs radically from "knowledge," this would radically affect Kant scholarship. Moreover, the implications go beyond the narrow confines of Kant exegesis. To be precise, Kant and his contemporaries seem to have used an entirely different epistemic category, namely "Erkenntnis," in addition to the categories used in philosophy today. Moreover, since Kant deemed "Erkenntnis" to be philosophically more significant than "knowledge," which is at the centre of contemporary epistemology, he quite probably also had different conceptions of the aims of our epistemic practices. During the proposed placement, I aim to find out whether Kant's immediate intellectual successor - the philosopher Johann Gottlieb Fichte - distinguished "Erkenntnis" from knowledge in an analogous way to Kant. Moreover, I intend to find out how Fichte's thoughts about the aims of epistemology differ from Kant's. Finally, I want to explore how Fichte's thoughts on this topic could be applied to both contemporary philosophy and some of society's current information processing challenges. The project will thereby contribute to a better understanding of why knowledge, truth and other epistemic practices are valuable and how we can promote these values. Moreover, it will contribute to filling a crucial gap in research on German Idealism.

The emerging era of exascale computing that will be ushered in by the forthcoming generation of supercomputers will provide both opportunities and challenges. The raw compute power of such high performance computing (HPC) hardware has the potential to revolutionize many areas of science and industry. However, novel computing algorithms and software must be developed to ensure the potential of novel HPC architectures is realized. Computational imaging, where the goal is to recover images of interest from raw data acquired by some observational instrument, is one of the most widely encountered class of problem in science and industry, with myriad applications across astronomy, medicine, planetary and climate science, computer graphics and virtual reality, geophysics, molecular biology, and beyond. The rise of exascale computing, coupled with recent advances in instrumentation, is leading to novel and often huge datasets that, in principle, could be imaged for the first time in an interpretable manner at high fidelity. However, to unlock interpretable, high-fidelity imaging of big-data novel methodological approaches, algorithms and software implementations are required -- we will develop precisely these components as part of the Learned EXascale Computational Imaging (LEXCI) project. Firstly, whereas traditional computational imaging algorithms are based on relatively simple hand-crafted prior models of images, in LEXCI we will learn appropriate image priors and physical instrument simulation models from data, leading to much more accurate representations. Our hybrid techniques will be guided by model-based approaches to ensure effectiveness, efficiency, generalizability and uncertainty quantification. Secondly, we will develop novel algorithmic structures that support highly parallelized and distributed implementations, for deployment across a wide range of modern HPC architectures. Thirdly, we will implement these algorithms in professional research software. The structure of our algorithms will not only allow computations to be distributed across multi-node architectures, but memory and storage requirements also. We will develop a tiered parallelization approach targeting both large-scale distributed-memory parallelization, for distributing work across processors and co-processors, and light-weight data parallelism through vectorization or light-weight threads, for distributing work on processors and co-processors. Our tiered parallelization approach will ensure the software can be used across the full range of modern HPC systems. Combined, these developments will provide a future computing paradigm to help usher in the era of exascale computational imaging. The resulting computational imaging framework will have widespread application and will be applied to a number of diverse problems as part of the project, including radio interferometric imaging, magnetic resonance imaging, seismic imaging, computer graphics, and beyond. The resulting software will be deployed on the latest HPC computing resources to evaluate their performance and to feed back to the community the computing lessons learned and techniques developed, so as to support the general advance of exascale computing.