The specialized training of health professionals in organ donation has turned to be one of the crucial factors for increasing donation rates in all countries. China the 2nd largest country in the world is facing the challenge of establishing an ethical and sustainable system of organ donation. The donation rate (PMP) was 2.02 in 2015, which is far behind when comparing with most of the countries in the world. Training for medical professionals is an effective approach to increase donation rate in China. Unfortunately, this work in training is far away from enough.Therefore; University of Barcelona, University of Bologna and University of Nice together with DTI-Foundation initiate KeTLOD project to fill-in the gap of the training lack in the Chinese universities on organ donation. This initiative is based on European great experience in donation activity and on the training of more than 10.000 health care professionals trained form the University of Barcelona through the Transplant Procurement Program since 1991 in this field.KeTLOD project will facilitate the design of a postgraduate program in organ donation field, for the Chinese health care professionals’ customized to their needs that will be implemented in 7 Universities. The KeTLOD curriculum is conceived as blended training program, in accordance with European Space for Higher Education guidelines and will offer knowledge and experience in clinical approach, management and dissemination strategies in Organ Donation. KeTLOD consist in a 625 hours program that will lead to 25 ETCS.KeTLOD will empower professional competences; enhance the detection and referral of potential donors and encourage a positive attitude towards donation in the society. KeTLOD; customized to the Chinese health professional needs, translated in Chinese language and shaped as blended training course, implemented in 7 crucial universities in terms of educational background and capacity and their geographical position will be a great

Harvesting the energy of sunlight offers a realistic, clean and sustainable solution towards energy generation with net-zero carbon emissions. Such aspiration has created an urgent need for a powerful catalogue of new inorganic or hybrid semiconductors to serve as cheap, efficient and stable light-harvesting materials for solar energy conversion. Particularly desirable are semiconductors enabling low energy pay-back time of fabricated light-harvesting devices, for example by material deposition from solution, low-temperature vapour deposition, or self-assembly of nanoscale building blocks. Intriguingly, many of these materials have recently been found to straddle the boundaries of "traditional" hard inorganic semiconductors (e.g. silicon) and classic "soft" molecular solids, opening up a complex array of exciting new fundamental science. The unusual properties displayed by such materials, including structural flexibility, strongly anharmonic lattice potentials, ionic migration, nanoscale assembly, or complex charge-screening processes are still poorly understood despite their critical impact on electronic properties and hence device performance. The overarching scientific aim of this Open Fellowship is to provide a paradigm shift in our fundamental understanding of the charge-lattice interactions that govern such effects. Specifically, the programme will reveal how interactions between photogenerated charge carriers and their surrounding ionic lattice affect parameters such as charge-carrier mobilities and recombination, and light-driven lattice instabilities that are critical to performance in energy-harvesting devices. Materials explored will expand from an initial selection of semiconducting metal halides, chalcohalides, metal chalcogenides, bisimides, and antimonides. Through observations across grouped materials clusters, this Fellowship programme will link charge-lattice interactions to attributes such as stoichiometry, electronic and structural dimensionality, lone-pair chemistry, structural flexibility, vibrational and dielectric response, lattice softness and anharmonicity, and ionic mobilities. Importantly, an examination of charge-lattice interaction across such a vast range of semiconducting materials in unison will enable patterns to be discernible that could not be discovered through work carried out on isolated materials. Through a powerful combination of advanced spectroscopic and structural techniques, this Fellowship will establish clear correlations and mechanisms linking core properties critical to efficient light-harvesting with basic material properties at an atomistic, electronic and structural level. This ambitious programme will further co-ordinate activities across a large number of Project Partners and collaborators, inspiring new synthetic activity and providing design tools urgently needed for computational materials screening. Overall, this Fellowship will tackle the complex array of exciting fundamental science arising in "soft" inorganic and hybrid semiconductors, seeking to develop new understanding to bridge the gap between existing models for well-established hard and soft semiconductors. The resulting discoveries will provide a blueprint for light-harvesting materials, guiding and accelerating the development of next-generation inorganic and hybrid crystalline semiconductors for the net-zero carbon transition. In addition, this Fellowship will serve as a springboard for advocacy in in the Net Zero area, through interactions with stakeholders, including policy makers, industrial partners, research councils, and learned societies. The Open Fellowship will also be leveraged to create an effective mentoring network for women in energy research in order to widen the talent pool in an area vital to planetary and human health.

Ensuring social, economic and environmental sustainability is one major aim of all the countries but priorities are not the same world over. The partner countries, China and Thailand, are fast growing economies attracting significant Foreign Direct Investment but facing a number of social and environmental challenges. Growing cities, expanding industry and increasing pollution of air, water and soil are big problems in both the countries which have several adverse effects on the society, environment and sustainable development.Applications of Geospatial technologies and methodologies in socio-economic analysis, natural resource management, economic planning, environmental management, sustainable developmental planning etc. have been well established during the last decades. However, Higher Education Institutions face a challenge of producing ‘ready-to-deliver’ Geospatial graduates.There are 3 main driving forces of Geospatial education i.e.:- Geospatial Application fields / Domains- Geospatial Data- Geospatial Technologies / ToolsThe interplay of the 3 driving forces is multilateral and reciprocal. The dynamics change in a matter of months, weeks and even in days requiring ‘fit-for-job‘ Geospatial workforce. However, HEIs fall behind in responding to the new job-requirements because they can't change curricula every month or year to incorporate new developments. As a result, by the time fresh graduates enter into the job-market, their skills are largely outdated or missing.The project envisages following outcomes:- Curricular structure, syllabi and teaching/learning materials of 20 problem-oriented case-studies based modules for PG level Geospatial study programmes.- 50 faculty members Professionally trained in delivering the modules.- 150 students with enhanced transversal skills through ‘hands-on’ practical experience of working with the applications of these modules.- An e-Learning platform facilitating free and open access to the modules worldwide.

In the UK and globally, the slope failures of various sizes are crucially affecting the sustainable development of resilient cities, as its occurrence can significantly threaten the populations, infrastructures, public services, and environment. For example, the British Geological Survey has estimated that 10% of slopes in the UK are classified as at moderate to significant landslide risk, with more than 7% of the main transport networks located in these areas. These slopes may fail during prolonged periods of wet weather or more intensive short duration rainfall events. To date, the public awareness of slope failure risk is high, but our understanding of its fundamental failure mechanism and countermeasures are still very limited. This is mainly due to the difficulties in analysing the multiscale responses and characterize the spatial inhomogeneity of material properties of slopes. Laboratory and numerical investigations with well-developed empirical models can explain the general features of some specific slope failure events but cannot be applied universally. Some challenging issues need to be addressed, such as i) How to develop reliable mathematical models with multiscale modelling capability to analyse the progressive failure of slopes? ii) How to address the spatial variabilities and uncertainties of real slopes, e.g. material property, fractures, fluid permeability? iii) How to accurately estimate the spreading of landslide and its impact on infrastructures? The fundamental scientific issue of these challenges is the weakening mechanism of inhomogeneous slopes at different scales as it determines the slope responses under various geological and environmental conditions. The proposed research aims to explore the fundamental mechanism of progressive slope failure and its impacts on infrastructures via a multiscale and probabilistic modelling approach. It enables the large deformation of slopes to be conveniently analysed by FEM as boundary value problem (BVP), while the local fracturing, cracking, or discontinuous behaviours of soil to be evaluated in smaller discrete subdomains through granular mechanics by DEM. The boundary condition of DEM assembly is derived from the global deformation of FEM meshes. In the analysis, the soil/rock properties (e.g. elastic modulus, friction coefficient, strength, and fluid permeability) will be evaluated as random fields with spatial variabilities. The numerical modelling can effectively bridge the gap between the microscopic material properties and the overall macroscopic slope responses. In the numerical modelling, the contributions of material inhomogeneity and discontinuity to slope failure and subsequence landslide spreading can be effectively investigated. The internal fracture would occur naturally when the loading stress exceeds the particle bonding strength at the microscale, which avoids the use of some phenomenological constitutive laws in conventional continuum modelling. As a multidisciplinary research, this project will involve the subjects of geotechnical engineering, computational geotechnics, geology, statistics, soil/rock mechanics and granular mechanics. The proposed numerical model will benefit all researchers and stakeholders in land planning and management by providing efficient and reliable numerical modelling approaches. This will support the landslide risk evaluation, hazard mitigation and long-term land management, from which the environmental, social, and economic benefits can be achieved. As a result, the decision makers would have greater confidence in slope failure risk assessments on which they are basing their infrastructure investment considerations. Consequently, hazard warning systems, protections and land utilization regulations can be implemented, so that the loss of lives and properties can be minimized without investing in long-term, costly projects of ground stabilization.

On a daily basis huge amounts of geospatial data and information that record location is created across a wide range of environmental, engineered and social systems. Globally approximately 2 quintillion bytes of data is generated daily which is location based. The economic benefits of geospatial data and information have been widely recognised, with the global geospatial industry predicted to be worth $500bn by 2020. In the UK the potential benefits of 'opening' up geospatial data is estimated by the government to be worth an additional £11bn annually to the economy and led to the announcement of a £80m Geospatial Commission. However, if the full economic benefits of the geospatial data revolution are to be realised, a new generation of geospatial engineers, scientists and practitioners are required who have the knowledge, technical skills and innovation to transform our understanding of the ever increasingly complex world we inhabit, to deliver highly paid jobs and economic prosperity, coupled with benefits to society. To seize this opportunity, the Centre for Doctoral Training in Geospatial Systems will deliver technically skilled doctoral graduates equipped with an industry focus, to work across a diverse range of applications including infrastructure systems, smart cities, urban-infrastructure resilience, energy systems, spatial mobility, structural monitoring, spatial planning, public health and social inclusion. Doctoral graduates will be trained in five core integrated geospatial themes: Spatial data capture and interpretation: modern spatial data capture and monitoring approaches, including Earth observation satellite image data, UAVs and drone data, and spatial sensor networks; spatial data informs us on the current status and changes taking place in different environments (e.g., river catchments and cities). Statistical and mathematical methods: innovative mathematical approaches and statistical techniques, such as predictive analytics, required to analyse and interpret huge volumes of geospatial data; these allow us to recognise and quantify within large volumes of data important locations and relationships. Big Data spatial analytics: cutting edge computational skills required for geospatial data analysis and modelling, including databases, cloud computing, pattern recognition and machine learning; modern computing approaches are the only way that vast volumes of location data can be analysed. Spatial modelling and simulation: to design and implement geospatial simulation models for predictive purposes; predictive spatial models allow us to understand where and when investment, interventions and actions are required in the future. Visualisation and decision support: will train students in modern methods of spatial data visualisation such as virtual and augmented reality, and develop the skills on how to deliver and present the outputs of geospatial data analysis and modelling; skills required to ensure that objective decisions and choices are made using geospatial data and information. The advanced training received by students will be employed within interdisciplinary PhD research projects co-designed with 40 partners ranging from government agencies, international engineering consultants, infrastructure operators and utility companies, and geospatial technology companies; organisations that are ideally positioned to leverage of the Big Data, Cloud Computing, Artificial Intelligence and Internet of Things (IoT) technologies that are predicted to be the key to "accelerating geospatial industry growth" into the future. Throughout their training and research, students will benefit from cohort-based activities focused on group-working and industry interaction around innovation and entrepreneurship to ensure that our outstanding researchers are able to deliver innovation for economic prosperity across the spectrum of the geospatial industry and applied user sectors.