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1,265 Projects

  • Canada
  • 2013-2022
  • OA Publications Mandate: No

10
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  • Funder: NIH Project Code: 5R01DA031043-05
    Funder Contribution: 1 USD
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  • Funder: UKRI Project Code: NE/K00008X/2
    Funder Contribution: 42,744 GBP

    Submarine landslides can be far larger than terrestrial landslides, and many generate destructive tsunamis. The Storegga Slide offshore Norway covers an area larger than Scotland and contains enough sediment to cover all of Scotland to a depth of 80 m. This huge slide occurred 8,200 years ago and extends for 800 km down slope. It produced a tsunami with a run up >20 m around the Norwegian Sea and 3-8 m on the Scottish mainland. The UK faces few other natural hazards that could cause damage on the scale of a repeat of the Storegga Slide tsunami. The Storegga Slide is not the only huge submarine slide in the Norwegian Sea. Published data suggest that there have been at least six such slides in the last 20,000 years. For instance, the Traenadjupet Slide occurred 4,000 years ago and involved ~900 km3 of sediment. Based on a recurrence interval of 4,000 years (2 events in the last 8,000 years, or 6 events in 20,000 years), there is a 5% probability of a major submarine slide, and possible tsunami, occurring in the next 200 years. Sedimentary deposits in Shetland dated at 1500 and 5500 years, in addition to the 8200 year Storegga deposit, are thought to indicate tsunami impacts and provide evidence that the Arctic tsunami hazard is still poorly understood. Given the potential impact of tsunamis generated by Arctic landslides, we need a rigorous assessment of the hazard they pose to the UK over the next 100-200 years, their potential cost to society, degree to which existing sea defences protect the UK, and how tsunami hazards could be incorporated into multi-hazard flood risk management. This project is timely because rapid climatic change in the Arctic could increase the risk posed by landslide-tsunamis. Crustal rebound associated with future ice melting may produce larger and more frequent earthquakes, such as probably triggered the Storegga Slide 8200 years ago. The Arctic is also predicted to undergo particularly rapid warming in the next few decades that could lead to dissociation of gas hydrates (ice-like compounds of methane and water) in marine sediments, weakening the sediment and potentially increasing the landsliding risk. Our objectives will be achieved through an integrated series of work blocks that examine the frequency of landslides in the Norwegian Sea preserved in the recent geological record, associated tsunami deposits in Shetland, future trends in frequency and size of earthquakes due to ice melting, slope stability and tsunami generation by landslides, tsunami inundation of the UK and potential societal costs. This forms a work flow that starts with observations of past landslides and evolves through modelling of their consequences to predicting and costing the consequences of potential future landslides and associated tsunamis. Particular attention will be paid to societal impacts and mitigation strategies, including examination of the effectiveness of current sea defences. This will be achieved through engagement of stakeholders from the start of the project, including government agencies that manage UK flood risk, international bodies responsible for tsunami warning systems, and the re-insurance sector. The main deliverables will be: (i) better understanding of frequency of past Arctic landslides and resulting tsunami impact on the UK (ii) improved models for submarine landslides and associated tsunamis that help to understand why certain landslides cause tsunamis, and others don't. (iii) a single modelling strategy that starts with a coupled landslide-tsunami source, tracks propagation of the tsunami across the Norwegian Sea, and ends with inundation of the UK coast. Tsunami sources of various sizes and origins will be tested (iv) a detailed evaluation of the consequences and societal cost to the UK of tsunami flooding , including the effectiveness of existing flood defences (v) an assessment of how climate change may alter landslide frequency and thus tsunami risk to the UK.

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  • Funder: CHIST-ERA Project Code: M2CR

    Communication is one of the necessary condition to develop intelligence in living beings. Humans use several modalities to exchange information: speech, written text, both in many languages, gestures, images, and many more. There is evidence that human learning is more effective when several modalities are used. There is a large body of research to make computers process these modalities, and ultimately, understand human language. These modalities have been, however, generally addressed independently or at most in pairs. However, merging information from multiple modalities is best done at the highest levels of abstraction, which deep learning models are trained to capture. The M2CR project aims at developing a revolutionary approach to combine all these modalities and their respective tasks in one unified architecture, based on deep neural networks, including both a discriminant and a generative component through multiple levels of representation. Our system will jointly learn from resources in several modalities, including but not limited to text of several languages (European languages, Chinese and Arabic), speech and images. In doing so, the system will learn one common semantic representation of the underlying information, both at a channel-specific level and at a higher channel-independent level. Pushing these ideas to the large scale, e.g. training on very large corpora, the M2CR project has the ambition to advance the state-of-the-art in human language understanding (HLU). M2CR will address all major tasks in HLU by one unified architecture: speech understanding and translation, multilingual image retrieval and description, etc. The M2CR project will collect existing multimodal and multilingual corpora, extend them as needed, and make them freely available to the community. M2CR will also define shared tasks to set up a common evaluation framework and ease research for other institutions, beyond the partners of this consortium. All developed software and tools will be open-source. By these means, we hope to help to advance the field of human language.

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  • Funder: EC Project Code: 314233
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  • Funder: UKRI Project Code: EP/V043811/1
    Funder Contribution: 497,214 GBP

    Coronaviruses are transmitted from an infectious individual through large respiratory droplets generated by coughing, sneezing or speaking. These infectious droplets are then transmitted to the mucosal surfaces of a recipient through inhalation of the aerosol or by contact with contaminated fomites such as surfaces or other objects. In healthcare settings, personal protective equipment (PPE) plays a crucial role in interrupting the transmission of highly communicable diseases such as COVID19 from patients to healthcare workers (HCWs). However, research has shown that PPE can also act as a fomite during the donning and doffing process as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can survive on these surfaces for up to three days. This creates a need for more effective PPE materials that can provide antiviral protection. In this proposal we aim to develop a dual action antiviral/antifouling coating to lower the risk of transmission of the SARS-CoV-2 to HCWs from COVID19 patients. This project will deliver antiviral/antifouling coatings that can be readily applied to PPE surfaces such as faceshields that are likely to encounter a high level of viral load and would be of great benefit to the health of clinical staff. Furthermore, this project has embedded into its planning a rapid pathway for optimisation, translation, and upscaling of manufacture to deliver a low-cost technology within a short timescale.

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  • Funder: NIH Project Code: 5R01AI053721-14
    Funder Contribution: 290,407 USD
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  • Funder: NIH Project Code: 5R25DA037756-09
    Funder Contribution: 371,402 USD
    more_vert
  • Funder: UKRI Project Code: EP/G036950/1
    Funder Contribution: 6,371,160 GBP

    This is an application for a Doctoral Training Centre (DTC) from the Universities of Sheffield and Manchester in Advanced Metallic Systems which will be directed by Prof Panos Tsakiropoulos and Prof Phil Prangnell. The proposed DTC is in response to recent reviews by the EPSRC and government/industrial bodies which have indentified the serious impact of an increasing shortage of personnel, with Doctorate level training in metallic materials, on the global competitiveness of the UK's manufacturing and defence capability. Furthermore, future applications of materials are increasingly being seen as systems that incorporate several material classes and engineered surfaces into single components, to increase performance.The primary goal of the DTC is to address these issues head on by supplying the next generation of metallics research specialists desperately needed by UK plc. We plan to attract talented students from a diverse range of physical science and engineering backgrounds and involve them with highly motivated academic staff in a variety of innovative teaching and industrial-based research activities. The programme aims to prepare graduates for global challenges in competitiveness, through an enhanced PhD programme that will:1. Challenge students and promote independent problem solving and interdiscpilnarity,2. Expose them to industrial innovation, exciting new science and the international research community, 3. Increase their fundamental skills, and broaden them as individuals in preparation for future management and leadership roles.The DTC will be aligned with major multidisciplinary research centres and with the strong involvement of NAMTEC (the National Metals Technology Centre) and over twenty companies across many sectors. Learning will be up to date and industrially relevant, as well as benefitting from access to 30M of state-of-the art research facilities.Research projects will be targeted at high value UK strategic technology sectors, such as aerospace, automotive, power generation, renewables, and defence and aim to:1. Provide a multidisciplinary approach to the whole product life cycle; from raw material, to semi finished products to forming, joining, surface engineering/coating, in service performance and recycling via the wide skill base of the combined academic team and industrial collaborators.2. Improve the basic understanding of how nano-, micro- and meso-scale physical processes control material microstructures and thereby properties, in order to radically improve industrial processes, and advance techniques of modelling and process simulation.3. Develop new innovative processes and processing routes, i.e. disruptive or transformative technologies.4. Address challenges in energy by the development of advanced metallic solutions and manufacturing technologies for nuclear power, reduced CO2 emissions, and renewable energy. 5. Study issues and develop techniques for interfacing metallic materials into advanced hybrid structures with polymers, laminates, foams and composites etc. 6. Develop novel coatings and surface treatments to protect new light alloys and hybrid structures, in hostile environments, reduce environmental impact of chemical treatments and add value and increase functionality. 7. Reduce environmental impact through reductions in process energy costs and concurrently develop new materials that address the environmental challenges in weight saving and recyclability technologies. This we believe will produce PhD graduates with a superior skills base enabling problem solving and leadership expertise well beyond a conventional PhD project, i.e. a DTC with a structured programme and stimulating methods of engagement, will produce internationally competitive doctoral graduates that can engage with today's diverse metallurgical issues and contribute to the development of a high level knowledge-based UK manufacturing sector.

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  • Funder: UKRI Project Code: NE/W004216/1
    Funder Contribution: 100,310 GBP

    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.

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  • Funder: UKRI Project Code: NE/K005421/1
    Funder Contribution: 337,728 GBP

    Variations in sea level have a great environmental impact. They modulate coastal deposition, erosion and morphology, regulate heat and salt fluxes in estuaries, bays and ground waters, and control the dynamics of coastal ecosystems. Sea level variability has importance for coastal navigation, the building of coastal infrastructure, and the management of waste. The challenges of measuring, understanding and predicting sea level variations take particular relevance within the backdrop of global sea level rise, which might lead to the displacement of hundreds of millions of people by the end of this century. Sea level measurement relies primarily on the use of coastal tide gauges and satellite altimetry. Tide gauges provide sea levels at fine time resolutions (up to one second), but collect data only in coastal areas, and are irregularly distributed, with large gaps in the southern hemisphere and at high latitudes. Satellite altimetry, in contrast, has poor time resolution (ten days or longer), but provides near global coverage at moderate spatial resolutions (10-to-100 kilometres). Altimetric sea level products are problematic near the coast for reasons such as uncertainties in applying sea state bias corrections, errors in coastal tidal models, and large geoid gradients. The complicated shoreline geometry means that the raw altimeter data have to either undergo special transformations to provide more reliable measurements of sea level or be rejected. Developments in GPS measurements from buoys are now making it possible to determine sea surface heights with accuracy comparable to that of altimetry. In combination with coastal tide gauges, GPS buoys could be used as the nodes of a global sea level monitoring network extending beyond the coast. However, GPS buoys have several downsides. They are difficult and expensive to deploy, maintain, and recover, and, like conventional tide gauges, provide time series only at individual points in the ocean. This proposal focuses on the development of a unique system that overcomes these shortcomings. We propose a technology-led project to integrate Global Navigation Satellite Systems (GNSS i.e. encompassing GPS, GLONASS and, possibly, Galileo) technology with a state-of-the-art, unmanned surface vehicle: a Wave Glider. The glider farms the ocean wave field for propulsion, uses solar power to run on board equipment, and uses satellite communications for remote navigation and data transmission. A Wave Glider equipped with a high-accuracy GNSS receiver and data logger is effectively a fully autonomous, mobile, floating tide gauge. Missions and routes can be preprogrammed as well as changed remotely. Because the glider can be launched and retrieved from land or from a small boat, the costs associated with deployment, maintenance and recovery of the GNSS Wave Glider are comparatively small. GNSS Wave Glider technology promises a level of versatility well beyond that of existing ways of measuring sea levels. Potential applications of a GNSS Wave Glider include: 1) measurement of mean sea level and monitoring of sea level variations worldwide, 2) linking of offshore and onshore vertical datums, 3) calibration of satellite altimetry, notably in support of current efforts to reinterpret existing altimetric data near the coast, but also in remote and difficult to access areas, 4) determination of regional geoid variations, 5) ocean model improvement. The main thrust of this project is to integrate a state-of-the-art, geodetic-grade GNSS receiver and logging system with a Wave Glider recently acquired by NOC to create a mobile and autonomous GNSS-based tide gauge. By the end of the project, a demonstrator GNSS Wave Glider will be available for use by NOC and the UK marine community. The system performance will be validated against tide gauge data. Further tests will involve the use of the GNSS Wave Glider to calibrate sea surface heights and significant wave heights from Cryosat-2.

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The following results are related to Canada. Are you interested to view more results? Visit OpenAIRE - Explore.
1,265 Projects
  • Funder: NIH Project Code: 5R01DA031043-05
    Funder Contribution: 1 USD
    more_vert
  • Funder: UKRI Project Code: NE/K00008X/2
    Funder Contribution: 42,744 GBP

    Submarine landslides can be far larger than terrestrial landslides, and many generate destructive tsunamis. The Storegga Slide offshore Norway covers an area larger than Scotland and contains enough sediment to cover all of Scotland to a depth of 80 m. This huge slide occurred 8,200 years ago and extends for 800 km down slope. It produced a tsunami with a run up >20 m around the Norwegian Sea and 3-8 m on the Scottish mainland. The UK faces few other natural hazards that could cause damage on the scale of a repeat of the Storegga Slide tsunami. The Storegga Slide is not the only huge submarine slide in the Norwegian Sea. Published data suggest that there have been at least six such slides in the last 20,000 years. For instance, the Traenadjupet Slide occurred 4,000 years ago and involved ~900 km3 of sediment. Based on a recurrence interval of 4,000 years (2 events in the last 8,000 years, or 6 events in 20,000 years), there is a 5% probability of a major submarine slide, and possible tsunami, occurring in the next 200 years. Sedimentary deposits in Shetland dated at 1500 and 5500 years, in addition to the 8200 year Storegga deposit, are thought to indicate tsunami impacts and provide evidence that the Arctic tsunami hazard is still poorly understood. Given the potential impact of tsunamis generated by Arctic landslides, we need a rigorous assessment of the hazard they pose to the UK over the next 100-200 years, their potential cost to society, degree to which existing sea defences protect the UK, and how tsunami hazards could be incorporated into multi-hazard flood risk management. This project is timely because rapid climatic change in the Arctic could increase the risk posed by landslide-tsunamis. Crustal rebound associated with future ice melting may produce larger and more frequent earthquakes, such as probably triggered the Storegga Slide 8200 years ago. The Arctic is also predicted to undergo particularly rapid warming in the next few decades that could lead to dissociation of gas hydrates (ice-like compounds of methane and water) in marine sediments, weakening the sediment and potentially increasing the landsliding risk. Our objectives will be achieved through an integrated series of work blocks that examine the frequency of landslides in the Norwegian Sea preserved in the recent geological record, associated tsunami deposits in Shetland, future trends in frequency and size of earthquakes due to ice melting, slope stability and tsunami generation by landslides, tsunami inundation of the UK and potential societal costs. This forms a work flow that starts with observations of past landslides and evolves through modelling of their consequences to predicting and costing the consequences of potential future landslides and associated tsunamis. Particular attention will be paid to societal impacts and mitigation strategies, including examination of the effectiveness of current sea defences. This will be achieved through engagement of stakeholders from the start of the project, including government agencies that manage UK flood risk, international bodies responsible for tsunami warning systems, and the re-insurance sector. The main deliverables will be: (i) better understanding of frequency of past Arctic landslides and resulting tsunami impact on the UK (ii) improved models for submarine landslides and associated tsunamis that help to understand why certain landslides cause tsunamis, and others don't. (iii) a single modelling strategy that starts with a coupled landslide-tsunami source, tracks propagation of the tsunami across the Norwegian Sea, and ends with inundation of the UK coast. Tsunami sources of various sizes and origins will be tested (iv) a detailed evaluation of the consequences and societal cost to the UK of tsunami flooding , including the effectiveness of existing flood defences (v) an assessment of how climate change may alter landslide frequency and thus tsunami risk to the UK.

    more_vert
  • Funder: CHIST-ERA Project Code: M2CR

    Communication is one of the necessary condition to develop intelligence in living beings. Humans use several modalities to exchange information: speech, written text, both in many languages, gestures, images, and many more. There is evidence that human learning is more effective when several modalities are used. There is a large body of research to make computers process these modalities, and ultimately, understand human language. These modalities have been, however, generally addressed independently or at most in pairs. However, merging information from multiple modalities is best done at the highest levels of abstraction, which deep learning models are trained to capture. The M2CR project aims at developing a revolutionary approach to combine all these modalities and their respective tasks in one unified architecture, based on deep neural networks, including both a discriminant and a generative component through multiple levels of representation. Our system will jointly learn from resources in several modalities, including but not limited to text of several languages (European languages, Chinese and Arabic), speech and images. In doing so, the system will learn one common semantic representation of the underlying information, both at a channel-specific level and at a higher channel-independent level. Pushing these ideas to the large scale, e.g. training on very large corpora, the M2CR project has the ambition to advance the state-of-the-art in human language understanding (HLU). M2CR will address all major tasks in HLU by one unified architecture: speech understanding and translation, multilingual image retrieval and description, etc. The M2CR project will collect existing multimodal and multilingual corpora, extend them as needed, and make them freely available to the community. M2CR will also define shared tasks to set up a common evaluation framework and ease research for other institutions, beyond the partners of this consortium. All developed software and tools will be open-source. By these means, we hope to help to advance the field of human language.

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  • Funder: EC Project Code: 314233
    visibility3
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  • Funder: UKRI Project Code: EP/V043811/1
    Funder Contribution: 497,214 GBP

    Coronaviruses are transmitted from an infectious individual through large respiratory droplets generated by coughing, sneezing or speaking. These infectious droplets are then transmitted to the mucosal surfaces of a recipient through inhalation of the aerosol or by contact with contaminated fomites such as surfaces or other objects. In healthcare settings, personal protective equipment (PPE) plays a crucial role in interrupting the transmission of highly communicable diseases such as COVID19 from patients to healthcare workers (HCWs). However, research has shown that PPE can also act as a fomite during the donning and doffing process as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can survive on these surfaces for up to three days. This creates a need for more effective PPE materials that can provide antiviral protection. In this proposal we aim to develop a dual action antiviral/antifouling coating to lower the risk of transmission of the SARS-CoV-2 to HCWs from COVID19 patients. This project will deliver antiviral/antifouling coatings that can be readily applied to PPE surfaces such as faceshields that are likely to encounter a high level of viral load and would be of great benefit to the health of clinical staff. Furthermore, this project has embedded into its planning a rapid pathway for optimisation, translation, and upscaling of manufacture to deliver a low-cost technology within a short timescale.

    visibility32
    visibilityviews32
    downloaddownloads20
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    more_vert
  • Funder: NIH Project Code: 5R01AI053721-14
    Funder Contribution: 290,407 USD
    more_vert
  • Funder: NIH Project Code: 5R25DA037756-09
    Funder Contribution: 371,402 USD
    more_vert
  • Funder: UKRI Project Code: EP/G036950/1
    Funder Contribution: 6,371,160 GBP

    This is an application for a Doctoral Training Centre (DTC) from the Universities of Sheffield and Manchester in Advanced Metallic Systems which will be directed by Prof Panos Tsakiropoulos and Prof Phil Prangnell. The proposed DTC is in response to recent reviews by the EPSRC and government/industrial bodies which have indentified the serious impact of an increasing shortage of personnel, with Doctorate level training in metallic materials, on the global competitiveness of the UK's manufacturing and defence capability. Furthermore, future applications of materials are increasingly being seen as systems that incorporate several material classes and engineered surfaces into single components, to increase performance.The primary goal of the DTC is to address these issues head on by supplying the next generation of metallics research specialists desperately needed by UK plc. We plan to attract talented students from a diverse range of physical science and engineering backgrounds and involve them with highly motivated academic staff in a variety of innovative teaching and industrial-based research activities. The programme aims to prepare graduates for global challenges in competitiveness, through an enhanced PhD programme that will:1. Challenge students and promote independent problem solving and interdiscpilnarity,2. Expose them to industrial innovation, exciting new science and the international research community, 3. Increase their fundamental skills, and broaden them as individuals in preparation for future management and leadership roles.The DTC will be aligned with major multidisciplinary research centres and with the strong involvement of NAMTEC (the National Metals Technology Centre) and over twenty companies across many sectors. Learning will be up to date and industrially relevant, as well as benefitting from access to 30M of state-of-the art research facilities.Research projects will be targeted at high value UK strategic technology sectors, such as aerospace, automotive, power generation, renewables, and defence and aim to:1. Provide a multidisciplinary approach to the whole product life cycle; from raw material, to semi finished products to forming, joining, surface engineering/coating, in service performance and recycling via the wide skill base of the combined academic team and industrial collaborators.2. Improve the basic understanding of how nano-, micro- and meso-scale physical processes control material microstructures and thereby properties, in order to radically improve industrial processes, and advance techniques of modelling and process simulation.3. Develop new innovative processes and processing routes, i.e. disruptive or transformative technologies.4. Address challenges in energy by the development of advanced metallic solutions and manufacturing technologies for nuclear power, reduced CO2 emissions, and renewable energy. 5. Study issues and develop techniques for interfacing metallic materials into advanced hybrid structures with polymers, laminates, foams and composites etc. 6. Develop novel coatings and surface treatments to protect new light alloys and hybrid structures, in hostile environments, reduce environmental impact of chemical treatments and add value and increase functionality. 7. Reduce environmental impact through reductions in process energy costs and concurrently develop new materials that address the environmental challenges in weight saving and recyclability technologies. This we believe will produce PhD graduates with a superior skills base enabling problem solving and leadership expertise well beyond a conventional PhD project, i.e. a DTC with a structured programme and stimulating methods of engagement, will produce internationally competitive doctoral graduates that can engage with today's diverse metallurgical issues and contribute to the development of a high level knowledge-based UK manufacturing sector.

    visibility54
    visibilityviews54
    downloaddownloads316
    Powered by Usage counts
    more_vert
  • Funder: UKRI Project Code: NE/W004216/1
    Funder Contribution: 100,310 GBP

    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.

    visibility58
    visibilityviews58
    downloaddownloads121
    Powered by Usage counts
    more_vert
  • Funder: UKRI Project Code: NE/K005421/1
    Funder Contribution: 337,728 GBP

    Variations in sea level have a great environmental impact. They modulate coastal deposition, erosion and morphology, regulate heat and salt fluxes in estuaries, bays and ground waters, and control the dynamics of coastal ecosystems. Sea level variability has importance for coastal navigation, the building of coastal infrastructure, and the management of waste. The challenges of measuring, understanding and predicting sea level variations take particular relevance within the backdrop of global sea level rise, which might lead to the displacement of hundreds of millions of people by the end of this century. Sea level measurement relies primarily on the use of coastal tide gauges and satellite altimetry. Tide gauges provide sea levels at fine time resolutions (up to one second), but collect data only in coastal areas, and are irregularly distributed, with large gaps in the southern hemisphere and at high latitudes. Satellite altimetry, in contrast, has poor time resolution (ten days or longer), but provides near global coverage at moderate spatial resolutions (10-to-100 kilometres). Altimetric sea level products are problematic near the coast for reasons such as uncertainties in applying sea state bias corrections, errors in coastal tidal models, and large geoid gradients. The complicated shoreline geometry means that the raw altimeter data have to either undergo special transformations to provide more reliable measurements of sea level or be rejected. Developments in GPS measurements from buoys are now making it possible to determine sea surface heights with accuracy comparable to that of altimetry. In combination with coastal tide gauges, GPS buoys could be used as the nodes of a global sea level monitoring network extending beyond the coast. However, GPS buoys have several downsides. They are difficult and expensive to deploy, maintain, and recover, and, like conventional tide gauges, provide time series only at individual points in the ocean. This proposal focuses on the development of a unique system that overcomes these shortcomings. We propose a technology-led project to integrate Global Navigation Satellite Systems (GNSS i.e. encompassing GPS, GLONASS and, possibly, Galileo) technology with a state-of-the-art, unmanned surface vehicle: a Wave Glider. The glider farms the ocean wave field for propulsion, uses solar power to run on board equipment, and uses satellite communications for remote navigation and data transmission. A Wave Glider equipped with a high-accuracy GNSS receiver and data logger is effectively a fully autonomous, mobile, floating tide gauge. Missions and routes can be preprogrammed as well as changed remotely. Because the glider can be launched and retrieved from land or from a small boat, the costs associated with deployment, maintenance and recovery of the GNSS Wave Glider are comparatively small. GNSS Wave Glider technology promises a level of versatility well beyond that of existing ways of measuring sea levels. Potential applications of a GNSS Wave Glider include: 1) measurement of mean sea level and monitoring of sea level variations worldwide, 2) linking of offshore and onshore vertical datums, 3) calibration of satellite altimetry, notably in support of current efforts to reinterpret existing altimetric data near the coast, but also in remote and difficult to access areas, 4) determination of regional geoid variations, 5) ocean model improvement. The main thrust of this project is to integrate a state-of-the-art, geodetic-grade GNSS receiver and logging system with a Wave Glider recently acquired by NOC to create a mobile and autonomous GNSS-based tide gauge. By the end of the project, a demonstrator GNSS Wave Glider will be available for use by NOC and the UK marine community. The system performance will be validated against tide gauge data. Further tests will involve the use of the GNSS Wave Glider to calibrate sea surface heights and significant wave heights from Cryosat-2.

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