devinitorg/iati-policy-markers huggingface dataset:
Modern African Nuclear DEtector LAboratory The University of York (UoY) nuclear applications group is presently running a one-year GCRF project called NuTRAIN with University of Western Cape (UWC) and University of Zululand (UZ) in South Africa. They are transferring expertise in working with scintillators and silicon photomultipliers which can be applied to applications in environmental monitoring, experimental nuclear physics and medicine. Six South African students have visited York to receive training and funds have been provided to establish small detector development laboratories at UWC and UZ. The present MANDELA project intends to build on this initial training in the form of a genuine distributed project to develop the components for a new and inexpensive type of positron emission tomography (PET) scanner for medical imaging. This will be based on plastic scintillator and make use of a newly developed UK-based supply chain for plastic scintillator established by LabLogic, a company based in Sheffield close by to UoY. Students in South Africa will be trained to carry out GEANT4 simulations - a method that allows the response of radiation detectors to be studied and hence, novel detectors can be designed. Importantly, UoY will provide these simulations "in the cloud" avoiding the need for high performance computers based locally. The simulations could even be run on a web browser or on a smartphone. Based on the simulations, prototype detectors will be fabricated. Based on training received at York, the SA students will evaluate these and determine the best silicon photomultipliers and fibre optic configurations for scintillation light detection. The MANDELA project will provide funding to upgrade their detector laboratory so they can undertake the necessary work. The project will lead to a solid design for the basic components of a novel PET scanner which can be pursued through a further collaborative R&D phase or move rapidly to commercialisation. The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
Development of bright laser-driven secondary sources toward applications for societal benefit In this proposal, we aim to develop next-generation technologies for extremely bright radiation and particle beams driven by intense lasers. In the near future these unique sources could be adopted for a wide range of advanced applications in healthcare, security and defence and industrial imaging. The advantage of the laser-driven source is its lower cost and smaller size compared to conventional accelerator machines. They can also be used to produce multiple, synchronised beams  from a single device. This makes them a powerful and affordable tool and one that can be widely deployed in industrial environments and hospitals. For example, tuneable beams of highly penetrating x-rays and neutrons could be used for multi-scale dynamic and tomographic imaging of large dense objects at unprecedented resolution. In the healthcare sector laser-driven x-ray beams could provide soft tissue imaging comparable in quality to that achieved at large-scale synchrotron facilities and also deliver electron and hadron beams to treat the cancer.   The wide-spread adoption of laser technology for these societal applications is a long term goal and the primary objective of this project is to establish a UK-India network to train young scientists in the methods necessary to operate such facilities. India has invested in state-of-the-art laser facilities and can attain a world-leading position in this growing field of applied science. The UK has long experience in high intensity laser development and implementation and we will work with our partnering Indian research institutes to maximise the output from their investment. Knowledge exchange and collaborative experiments in this research area will be highly beneficial to both the Indian and UK high power laser research communities. As these high-profile Indian laser institutes develop they will encourage young people to pursue scientific careers and attract investment from industrial sources with challenges that can be addressed by this technology. The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
From Stars to Baht: Broadening the economic impact of astronomical data handling techniques in Thailand - Phase II The most effective way of reducing levels of poverty in developing countries is through their continued economic development, which leads to increased levels of income per person. Research has shown that one of the main ways of achieving this is through maintained increases in levels of productivity (defined as output per hour worked) within businesses and organisations. For an upper-middle income economy such as Thailand's, productivity growth will increasingly rely on innovation, which today requires access to high-tech skills. With more and more Thai industries collecting data on their customers, production lines, distribution networks, stock prices, etc., one of the most crucially needed high-tech skill is the ability to handle large amounts of digital data. Our ongoing project aims to provide such skills for businesses and organisations across Thailand, especially those regions outside Bangkok which have traditionally suffered from weaker economic growth. The first step in this project - for which we received Newton funding - was to use large astronomical datasets to expose Thai data scientists based at Mae Fah Luang University (MFU) to "Big Data". This was followed by a GCRF Foundation Award to facilitate working with five pre-selected regional businesses and organisations, during which we worked with undergraduate students to research how to adapt our technologies and skills to meet the data handling and analysis needs of these external partners. Following the success of our Foundation Award project, we now request GCRF funds to support the expansion of the project to include a broader range of larger external partners with a more national presence. This will provide MFU with the exposure needed to become a self-sustaning hub for data science research and training within Northern Thailand. The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
Official Development Assistance Institution Awards New database technologies with the National Astronomical Institute of Thailand; web based astro-ecology software toolset to allow access in developing counties; web based image processing to allow international access in secondary schools. The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
Official Development Assistance Institution Awards Strengthen collaboration in Nuclear Physics between physicists in UK & African nations; transfer knowledge and skills between the collaborating parties;  provide opportunities for education and training for African nations The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
ASTEC: Astronomical System Training, Engineering and Collaboration The Large Millimetre Telescope (LMT) is Mexico's largest ever investment in a science facility. The project proposed here will help train Mexican astronomers in the high frequency radio techniques necessary to build receivers for use on LMT. This training will be carried out by converting an existing "SHIRM" receiver previously used for Earth observations for use on the LMT for astronomical observations. The skills transferred to the Mexican community during this project have wide ranging application to other research and commercial applications which have direct impact on development. Examples include atmospheric and ground-use monitoring, and active sensors in a range of applications including on cars, an area in which Mexico has a large manufacturing sector.    This proposal is the child of the University of Manchester Proposal ASTEC (ST/R002843/1) The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
From Stars to Baht: Broadening the economic impact of astronomical data handling techniques in Thailand The most effective way of reducing levels of poverty in developing countries is through their continued economic development, which leads to increased levels of income per person. Research has shown that one of the main ways of achieving this is through maintained increases in levels of productivity (defined as output per hour worked) within businesses and organisations. For an upper-middle income economy such as Thailand's, productivity growth will increasingly rely on innovation, which today requires access to high-tech skills. With more and more Thai industries collecting data on their customers, production lines, distribution networks, stock prices, etc., one of the most crucially needed high-tech skills is the ability to handle large amounts of digital data. Our ongoing project aims to provide such skills for businesses and organisations in the Northern region of Thailand which has traditionally suffered from weaker economical growth compared to other regions such as Bangkok. The first step in this project -- for which we received Newton funding -- was to use large astronomical datasets to expose Thai data scientists and their postgraduate students to "Big Data". Following the success of that first stage, we now request GCRF funding to facilitate working with five pre-selected businesses and organisations to research how we can adapt the technologies and skills we have developed to meet their data handling and analysis needs. In doing so, we will be using our team's skills and technologies to have a real economic impact on these external partners, while we build our capacity for working with businesses and organisations. This experience will be excellent preparation for our ultimate goal of establishing a fully self-sustaining "Centre of Excellence" for researching technologies to meet the data handling and analysis needs of businesses and organisations in Northern Thailand. The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
Official Development Assistance Institution Awards ODA Institutional Award. Integrating advanced earth observation and environmental information for sustainable management of crop pests and diseases in China. The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
Applying Astronomy Data Analysis to enhance disaster forecasting Livestock accounts for 37.5% of Kenya's land area, 12% of its GDP and 40% of its agricultural sector, but is susceptible to frequent droughts and periods of overgrazing. In this context, this project will assess the potential of new Earth observation datasets to deliver near real-time monitoring and prediction of useful and accessible biomass for pastoralism.  Drought and flood events are a major threat in sub-Saharan Africa (SSA) causing substantial losses of life, assets and livelihoods, and weakened national economic performance. Hazard early warning and disaster risk preparedness actions can be effective in reducing these losses (as much as 20 times more effective than post-disaster relief). In this project we will apply advanced data analysis techniques used in astronomy to facilitate improved hazard early warning models in Kenya.   This pilot project brings together STFC funded Astronomers at University of Sussex with a strong track record in data analysis with a world-leading interdisciplinary team in Climate Change and Developmental studies.   Several global to regional pasture monitoring systems exist that are based on Earth observation data, which are used in early warning systems. These systems tend to rely on coarse resolution data (250m - 8km) to provide near real-time information on vegetation health, and are combined with mechanistic models or expert knowledge to forecast seasonal outcomes. However, this spatial scale is unable to adequately distinguish pastures from scrublands, small farms and woody vegetation, and is unable to provide meaningful information on the onset of vegetation stresses. This project will use data from the Copernicus Sentinel mission (data provided every 5-12 days at 10-20m resolution) with key information on vegetation state.  The ultimate outcome of this research will support pastoralists communities Kenya, to decide the suitability and location of pastureland for their various livestock through: a) improved understanding of spatio-temporal distribution of pastures; b) improved understanding of ecological changes and resilience of pastures; and c) near-future predictions of pasture suitability. This will enhance their livelihood resilience in the wake of large and extensive droughts, overgrazing, and land cover change. The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
Official Development Assistance Institution Awards Develop machine learning model of crop growth, based on the approach developed at UCL. Trained on satellite observations in China, and validated against field data. Powerful, generic approach to detecting crop phenology (growth stage and rate) The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
China-United Kingdom Joint Square Kilometer Array Programme UK-China Square Kilometre Array Researcher Exchange Scheme to build capacity in China by training early career researchers in the use of the Square Kilometre Array as well as in data processing. The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
Official Development Assistance Institution Awards Training in Astronomical Research and Education. Capacity building in India/Nepal, lectures on astrophysics &data science. Core learning, outreach activities, hands-on training & cross-border interactions to develop the next generation of researchers The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
SA-DISCNet: A collaborative data science training network across southern Africa and southern UK Data intensive science is a major global growth area, as the volume, complexity and rate of digital data within governments and companies continues to rapidly increase. At the same time, powerful analysis techniques continue to evolve for obtaining radical insights into large datasets, including finding clusters and anomalies, as well as detecting and predicting dominant trends and correlations in such data. This data intensive science comes at a crucial time for global development. Major worldwide challenges, as encapsulated in the United Nations' Sustainable Development Goals (SDGs), require multidisciplinary solutions, many of which include data science. Moreover, the South African National Development Plan (NDP) for 2030 recognises the need to "sharpen its innovative edge and continue contributing to global scientific and technological advancement" and "shift to a more knowledge-intensive economy".    We therefore propose to build a training network in data intensive science between universities in southern UK and partners in southern Africa to help address these SDGs and NDP priorities. The cornerstones of this network will be the `Data Intensive Science Centre in SEPnet' (DISCnet) and the African Institute of Mathematical Science (AIMS) South Africa. Together, we will pilot an innovative course of training and internships for the next generation of data analysts, focusing on solving SDG-related questions in South Africa and acting as a driver of the country's economy in the 21st century.   Our aim with this pilot training programme is to equip and send students to solve data science problems associated with sustainable development goals (SDGs) in SA and beyond. The specific goals of the pilot programme are to: (i) Deliver an initial cohort of at least 10 highly trained African data scientists; (ii) Provide a world-class data science school to African students, leveraging existing DISCnet training material; (iii) Prime-pump a new 8-week hand-on data science training course at AIMS with contributions from DISCnet; (iv) Contribute to the sustainable development goals via 3 month strategic student internships with South African organisations and companies, focusing on economic development and welfare; (v) Understand the details of managing an extended, sustainable training network across southern Africa.  This pilot leverages considerable investment from STFC, our university partners, and the Royal Society (RS). Our long-term ambition is to create a sustainable network of comparable scale to DISCnet, e.g. approximately 25 African STEM students per year receiving our specialist training. These students will become the future data science leaders in Africa. The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
Astro-ecology: the solution from the skies to save Earth's biodiversity The long-term goal of this project is to build upon STFC-funded innovations in astronomy to help tackle challenges to developing countries identified in the Global Challenge Theme Areas, "Sustainable Resources" and "Sustainable Growth". Over the last 18 months we have demonstrated that software developed by astronomers to detect emission and identify objects in thermal (mid-infrared, wavelength ~10 micron) wavelength astronomical images is extremely well suited to identifying and characterising animals in aerial thermal video footage. Last year we were awarded  STFC 21st Century Challenge pump priming funds to support a Postdoctoral Research Assistant (PDRA) for 9 months to develop the automated source-finding and identification software pipeline we created to work in different ecosystems. We have subsequently published a pilot paper based on this work. The press release associated with the paper was picked up by media outlets word-wide. As a result, we have received requests from many conservation organisations in developing countries asking to use our drone + software pipeline system. Having demonstrated that this has the potential to be a cost-effective and efficient way to monitor and help manage animal populations over large areas, we now request funding to (i) help the stakeholders who have contacted us, (ii) thereby demonstrate this approach can tackle some of the major challenges facing developing countries, such as food security, animal health and ecosystem monitoring/protection/conservation, and (iii) begin systematically tackling these challenges in developing countries around the world. The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
Official Development Assistance Institution Awards Using Astronomy Data Analysis to enhance disaster forecasting. High resolution data used to determine suitability, location of pastureland to enhance livelihood resilience in the wake of large and extensive droughts, overgrazing& land cover change The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
Exploration and concept 2016 Developing a road map to identify requirements and priorities for satellite product development to forecast and understand air quality problems caused by land and forest fires impacting the environment, crops and health in South East Asia The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
Remote Sensing for sustainable use of seasonally dry tropical forests - Learning to live with the forest Monitor biodiversity and assess ecosystem quality to protect seasonally dry tropical forests. This project looks particularly at the Caatinga area of Brazil. The techniques developed will benefit all countries with a similar forest areas. SDG: 15 The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.
Official Development Assistance Institution Awards Develop and test the agri-tech in Chinese farms, organise stakeholder workshops to promote agri-tech, bring leading Chinese scientists to Newcastle University for 1-2 weeks to develop stronger partnerships. The Global Challenges Research Fund (GCRF) supports cutting-edge research to address challenges faced by developing countries. The fund addresses the UN sustainable development goals. It aims to maximise the impact of research and innovation to improve lives and opportunity in the developing world.