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MJN Neuroserveis’ has developed SERAS, a non-invasive, discrete and wearable device that predicts an epileptic seizure before it occurs. The device consists of an earpiece that reads the electroencephalogram, and a cloud-connected mobile application containing an artificial intelligence algorithm that alerts the user, their environment, and medical services one minute before a seizure occurs. In addition, the device permanently monitors a patient's brain activity, allowing for the generation of medical reports, the number of seizures suffered, their intensity and frequency. Currently, doctors who care for these patients do not have the data to allow for targeted patient treatments. Today, there is no device clinically validated in the market with these functionalities that can permanently monitor brain activity in a discrete, portable and continuous way. Around 50-65 million people suffers from epilepsy worldwide, depending on source. These people live in a permanent state of uncertainty, caused by not knowing when they will suffer the next seizure and if it could cause a serious accident for them. SERAS is a disruptive solution unique in monitoring brain signals and predicting epilepsy seizures with enough time to avoid accidents. MJN is a business moved by high social impact vision; our claim is ‘Quality of life for everybody’. We face a market of 6 million epileptic people in EU and USA. We aim to become a new benchmark on a global scale in the digital health world related with neurological diseases. SME Instrument Ph2 project will help us to improve our prediction algorithm in order to automate learning process and create a platform to exploit data recorded from users of the device. This will allow us and doctors go a step further on research of neurological pathologies. By Ph2 project we will accelerate our commercialization plan to scale-up our business to the goal of €27 million turnover by 2025.

The FORCOAST project addresses the topic “DT-SPACE-01-EO-2018-2020 COPERNICUS MARKET UPTAKE” which seeks to foster market development exploiting the value of Copernicus Earth Observation Products. FORCOAST aims to provide information services that offer high resolution water quality and met-ocean indicators in coastal and nearshore areas, to improve operation, planning and management of different marine activities in the sectors of wild fisheries, oystergrounds restoration, and bivalve mariculture. FORCOAST information products and services will be co-designed with stakeholders, thereby ensuring that these products and services are tailored to meet their needs. FORCOAST is developing, testing and demonstrating, in operational mode, novel Copernicus-based downstream information services that will incorporate Copernicus Marine, Land and Climate Services Products, local monitoring data and advanced modelling in the service. The services will integrate Copernicus Earth Observation Products with local models and other diverse data sources (local, regional or global) with ICT (enhancing new frontiers opened by web, and use of cloud) across the different market segments. FORCOAST will provide consistent coastal data products, based on a standardized data processing scheme. FORCOAST is supporting the concept of developing an advanced platform and cloud computing for Copernicus-based downstream services utilizing one of the DIAS systems. The availability and accessibility of data and derived products generated will stimulate their exploitation by a wide range of user communities in the targeted sectors. FORCOAST will provide those services in eight pilot service uptake sites covering five different regional waters (North Sea, Baltic Sea, Mediterranean Sea, Black Sea and the coastal Atlantic Ocean).

This qualitative pilot study aims to provide insight into an under-developed area by exploring health inequalities amongst substance users from different class position living in the north east of England. This study will develop a theoretical approach which offers a way of conceptualising the connection between social inequality, health inequality and substance use practices drawing on Bourdieu (1990) and other relevant theorists. This involves challenging public health doxa which frames health inequalities as structural or caused by individual risk behaviours. The importance of this research is linked to an agenda for social justice and a government priority in England to reduce inequalities to allow everyone to have the same opportunities to lead a healthy life (PHE, 2017). Illicit substance users come from a range of social class backgrounds and genders; yet, we do not know how a substance users’ place in society impacts on their health or their drug use. Using qualitative semi-structured interviews this study will firstly, explore the relational connection across class, gender and substance use by providing insight into the experiences of a diverse range of individuals’ and their everyday lives, and secondly, identify emerging health inequalities and how they are (re)produced.

Our understanding of how the immune system shapes the development of cancer is constantly improving as we continue to employ better experimental models. In particular, we are interested in how cytotoxic T cells, known as “resident killer” cells of the immune system, are capable of entering tumour tissues to suppress malignant cell growth. Acquisition of mutations allows tumour cells to become insensitive to soluble molecules called cytokines, which function within the vicinity of the tumour to promote T cells to recognize and attack tumour cells. Inflammatory cytokines further activate professional antigen presenting cells which can in turn initiate T cells specific for the tumour to proliferate and persist. However, it is not known whether insensitivity to cytokines due to tumour mutations will alter the function of immune cells. We propose to explore this biology using a murine model of melanoma which best replicates immune cell activity in the tumour. We aim to better understand how these mutations dampen anti-tumour immunity, and hope that our results can provide the basis for novel therapies which work to re-shape immune responses against tumours.

The human subcortex is a highly crowded brain area, which consists of hundreds of unique, small grey matter nuclei constituting approximately ¼ of total human brain volume. Importantly, only approximately 7% of these nuclei are currently accessible in standard human brain magnetic resonance imaging (MRI) atlases (Forstmann et al., 2016). This low percentage can have several imaging related causes, including the small size of subcortical nuclei as compared to the voxel size, which is particularly relevant when applying 1.5 or 3 Tesla (T) MRI. Additionally, the challenges posed by the large distance of the subcortex from the head coil may be a cause. In light of the vast amount of uncharted brain areas, one can also think of the human subcortex as ‘terra incognita’. The aim of this proposal is to chart ‘terra incognita’ to create a tool to identify and localize new targets for DBS. Major efforts of my group have already been directed towards resolving at least part of the challenges of imaging the human subcortex through the development of ultra-high field resolution 7T magnetic resonance imaging (UHF-MRI) sequences tailored to image the subcortex. Within our project ‘Atlasing the human subcortex’, collaborations with world-leading companies in DBS technology such as Boston Scientific (http://www.vercise.com/index.cfm) have been established. Here, we aim to extend these efforts by applying for funding for research personnel that will execute the manual segmentations and validation of new potentially more efficient target areas for DBS neurosurgery. These efforts will lead to creating probabilistic atlas maps for DBS surgery with unprecedented detail as well as a 3D app for educational purposes both in the clinical and basic neurosciences. These efforts will ultimately lead to commercial products that have already attracted attention of world-leading DBS companies.

The neuromesodermal progenitors (NMPs) are a group of cells found in the developing embryo, which form the spinal cord and surrounding muscle. NMPs are present at the tail end of the embryo, first producing the head, then trunk and finally the tail end, changing the genes they express as they do this. A subset of these time-regulated genes includes the HOX genes, named HOX1-HOX13. At early stages, NMPs poised to make the neck express HOX1, while successively later NMPs that make the trunk and tail progressively express more of the genes until HOX13 is expressed in tail tip. Studies removing these genes showed that each one is necessary to make vertebrae of a particular identity. It is unknown whether the expression of HOX genes in NMPs at different times during development is important to set identity. It is currently only possible to make NMPs in culture with neck and upper trunk identity. Therefore, I hope to develop a method to make human NMPs which express all the Hox codes. Once we have done this, we will research what is controlling how the cells gain Hox identity. Finally, I will research if HOX code controls NMP differentiation when placed into embryos.

The general objective of the project is the development of an integrated planning tool for multi-energy systems on a European scale. To reach the COP21 goals concerning a stepwise reduction of energy-related greenhouse gas (GHG) emissions in a cost effective way, the decarbonisation of multiple energy sectors is necessary. Therefore, the model considers the coupling of different energy sectors (electricity, heat, mobility and gas) and calculates the cost-optimal energy mix for the future European energy system (e. g. up to 2050) that is compliant with the climate goals. Besides generation and storage systems, also transmission and distribution grids are considered in the planning and operation stage in an integrated way. These modeling requirements lead to both a large mixed-integer (non-linear) optimization problem and new solution methods that will be developed within the course of the project. This will be achieved by solving both mathematical and computational challenges in the field of energy system modeling. Thereby, novel mathematical formulations of energy system modeling problems will be proposed, e. g. by combining diverse mathematical decomposition methods. The goal is to strive towards a system, where a multiplicity of models for single energy system aspects all synergistically contribute to the optimal planning of such a complex system. The project will provide a new energy system planning tool for different stakeholders of the energy system, which promotes optimal development and operation of the system. This includes European system planners, regulators and national authorities as well as technology companies, grid operators and utilities. To ensure the applicability of the developed tools, an advisory board will review the intermediate and final results of the project. Finally, two case studies with European scope will be performed to show the adequacy and relevance of the developed modelling framework.

Resilience is defined by the United Nations as “the ability to resist, absorb and accommodate to the effects of a hazard, in a timely and efficient manner”. Thus, resilient communities are those in which their citizens, environment, businesses, and infrastructures have the capacity to withstand, adapt, and recover in a timely manner from any kind of hazards they face, either planned or unplanned. In recent years efforts have been spent to tackle resilience and there is, still, a long path forward in defining an EU valid and sound approach to the problem. RESILOC aims at studying and implementing a holistic framework of studies, methods and software instruments that combines the physical with the less tangible aspects associated with human behaviour. The study-oriented section of the framework will move from a thorough collection and analysis of literature and stories from the many approaches to resilience adopted all over the World. The results of the studies will lead to the definition of a set of new methods and strategies where the assessment of the resilience indicators of a community will be performed together with simulations on the “what-if” certain measures are taken. These studies and methods will serve for designing and implementing two software instruments: 1. the RESILOC inventory, a comprehensive, live, structure for collecting, classifying and using information on cities and local communities, implemented as a Software as a Service (SaaS). 2. The RESILOC Cloud-based platform for assessing and calculating the resilience indicators of a city or a community, for developing localised strategies and verifying their impacts on the resilience of the community. The Cloud platform, a combination of SaaS and PaaS, includes the inventory as its repository. The project will make use of built solutions in four field trials and includes a high-profile communication plan, heavily based on Social Media platforms.

Creating battery-free “self-sustaining” sensor systems is a key requirement to realising the forecasted billions of interconnected sensors within the Internet of Things. Micro energy harvesting, scavenging energy from the ambient environment, through the use of autonomous micro energy sources (AMES), is an ideal solution; avoiding the need for regular battery replacement. Along with energy harvesters and energy storage, the major component in an AMES solution is an Energy Management Integrated Circuit (EMIC). The key technical challenges are that each type of energy-harvester has very different electrical characteristics and that the ambient energy is not available all of the time. A single EMIC is required that can effectively harvest from any energy harvester type. No such EMIC exists today. At Trameto, we are developing a patent protected portfolio of EMICs named ‘HarvestAll’. These devices will deliver any-many-multi energy harvesting functionality to permit applications to harvest all types of ambient energy now, enable the design and development of next generation AMES, and allow the creation of novel AMES applications that were not previously possible. HarvestAll products will be exported to global customers with whom we have built strong relationships through strategic and aggressive business development activities with the support of H2020, Innovate UK, and private seed-funded projects. Through our customer interactions, we have developed a number of fully qualified, early revenue case study opportunities which will allow us to showcase the functionality of our HarvestAll portfolio.

Urban and peri-urban agriculture (UA) has emerged as a more sustainable alternative to produce food. UA has several types of emerging systems (ES) that are exponentially growing from an experimental to an industrial scale of development. UA-ES include vertical farming, integrated greenhouse rooftops in buildings, local woodsheds, etc. UA-ES are expected to reach mature levels of development in the mid to long-term future and are being designed to recirculate and minimise the use of resources (e.g. nutrients, water, substrates and CO2) for production of low carbon intensity food in cities, among other benefits. Therefore, it is expected that UA-ES will provide more sustainable food production compared to rural, more-traditional agriculture systems in terms of energy and water use as well as benefits for air quality and biodiversity in cities. Understanding and quantifying the effective contribution that UA-ES will make to the environmental sustainability of cities requires the ability to both evaluate UA-ES environmental impacts in the future and to compare them to the impacts of traditional agriculture in the same future context. The project PROspecTive Environmental AssessmeNt of Urban Agriculture-Emerging Systems (PROTEAN) will focus on developing temporally-explicit environmental impact assessment models for both UA-ES and traditional agriculture to determine the extent to which UA-ES may contribute to the sustainability of future food production. These ex-ante, temporally-explicit environmental impact assessments will also help to flag influenceable system parameters that can make UA-ES more environmentally sustainable in the future. Thus, future undesired environmental impacts, costs, and effects may be more easily avoided for UA-ES than for mature agriculture systems. Providing assertive guidance on how to improve UA-ES depends on our current capacity to understand the key leavers of change that may drive the future impacts of these systems.