1,494 Projects, page 1 of 150

  • European Commission
  • 2020
  • 2022

  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 888777
    Overall Budget: 184,591 EURFunder Contribution: 184,591 EUR
    Partners: RCSI

    Polymer hydrogels contain over 90% water and are very useful materials in many biomedical areas such as contact lenses, drug delivery, wound healing, among others. However, many hydrogels are mechanically underperforming in that they are either too weak or too brittle. Double network hydrogels have shown significant promise to overcome this issue and mechanically strong or stretchable, elastic double network hydrogels have been reported. The overall aim of this project is to develop a new class of stretchable biocompatible double network hydrogels based on polypeptides as patches for transdermal drug delivery. The project will develop novel chemistry to achieve materials with enhanced properties validated for a drug delivey application by a multidisciplinary approach combining expertise in polymer chemistry, material science, drug delivery and biomaterial science. The project will foster new collaboration opportunities between research groups from different scientific fields. The high-level science is complemented by bespoke training activities, which will significantly advance the career opportunities of the applicant. A particular feasture of the project is the proposed development of a hydrogel school experiment in collaboration with the teachers-in-residence programme of the Irish Centre for Medical Device (CURAM) to foster scientific interest, motivation and encouragement for pupils in schools located in disadvantaged communities. Moreover, commercial exploitation of the scientific findings and developments will be explored.

  • Open Access mandate for Publications
    Funder: EC Project Code: 957468
    Funder Contribution: 150,000 EUR
    Partners: University of Gothenburg

    The goal of Lucero is to create autonomous micromanipulation solutions for biological applications integrating optical manipulation, microfluidics, and machine intelligence. Single-cell analysis is critical in many biomedical applications, such as clinical trials, in-vitro fertilization, forensic analysis, and single-cell omics. In fact, it is an ideal moment to enter the single-cell analysis market, because this market is valued at $1.4 billion globally and expected to keep on growing with a compound annual rate higher than 17%. While some techniques are already commercially available, single-cell approaches still have several limitations. Mechanical tools (e.g., motorised micropipettes and microneedles, centrifugation) are invasive and prone to damage the cells. Labeled-sorting methods (e.g., flow-cytometry) can affect cell viability for subsequent protocols. Non-invasive sorting procedures based on microfluidics require high amounts of cells and numerous repetitions to obtain a significant fraction of target cells. Furthermore, in all cases these methods require expert handling and are labor intensive. With Lucero, we propose a solution that overcomes these problems based on a smart optofluidic platform: contactless thanks to the use of optical tweezers, capable of controlling the local cellular environment thanks to the use of microfluidics, and capable of autonomous and accurate operation thanks to machine intelligence. Lucero will be compatible with standard microscopes already available in biomedical laboratories, permit to completely automatize single-cell protocols, and therefore drastically lower the cost of biomedical research. Lucero already counts with an outstanding core team of scientists and experienced business people, and it will provide ~20 jobs to university-educated individuals in the EU within the next 5 years. Lucero has already received initial funding and support from two different organizations that support and believe in Lucero's venture.

  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 888997
    Overall Budget: 196,708 EURFunder Contribution: 196,708 EUR

    Programming the autonomous and multiscale structuring of shapeless synthetic soft matter is unknown and conceptually challenging. In stark contrast, a living embryo is highly ordered at all levels – from cells to the entire organism. The ordering is a multistep process, starting from the patterning of biomolecules (morphogens) which later instruct autonomous shape transformations (morphogenesis). Inspired by these natural physicochemical processes, we aim at the preparation of a first-ever synthetic biocompatible material which can be self-organized in a programmable and autonomous manner. The programming will be achieved by an out-of-equilibrium DNA-based chemical network which predictably generates single-stranded DNA morphogens. Combined with diffusion, the concentrations of the morphogen can be patterned with a unique spatiotemporal precision, including travelling waves and stable fronts, which were pioneered by the host group. The autonomy of morphological structuring will be accomplished by linking the mechanical activity of active gels, composed of DNA-kinesins and microtubules, to the presence of the DNA morphogen. Latter will act as a cross-linker creating the clusters of kinesins and thus guiding the self-organization of the soft material by the collective action of nanoscale kinesin motor proteins which exert force on microtubules. Apart from the preparation of a first biocompatible man-made morphogenetic material, we will learn how the self-organization of active gels is dependent on morphogens’ patterns. This knowledge is indispensable for the advanced programming of the precise macroscale shapes at the molecular level of chemical networks, which are diverse and modular. With further developments, our methodology could lead to so far elusive self-fabricated, force-exerting synthetic soft matter with the potential of integration in soft robotics and biological environments.

  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 897873
    Overall Budget: 147,815 EURFunder Contribution: 147,815 EUR
    Partners: NOVA

    Deductive software verification, a subject within the broader field of formal methods, proposes a very ambitious path: to turn the correctness of a computer program into a mathematical statement, and then prove it. This project aims to develop a deductive verification framework, with a clear focus on proof automation, that directly tackles the verification of OCaml-written programs. OCaml seems to be particularly good target for verification. On one hand, it is the language of choice for the implementation of sensible software such as proof assistants, automated solvers, and compilers. On the other hand, OCaml is a multi-paradigm language, supporting both the functional and imperative paradigm, one can write clean, concise, type-safe, and efficient code. Yet, a verification tool that can handle hand-written code and is mostly automated does not currently exist. OCaml programmers must chose between proof automation, with the price of learning and programming in a verification-aware language, and then perform code extraction, or tools that require manual proof assistance. The Cameleer project aims to remedy this situation by providing the tools and principles for the verification of OCaml programs. The main outcome of this project is a powerful, usable, and mostly automated verification framework for the OCaml-written code. This will be a major step towards making verification more accessible to OCaml programmers, even in case they are not verification experts. The Cameleer framework will feature a translation of OCaml programs annotated with specifications written in GOSPEL, a recently proposed specification language, to different intermediate verification languages, namely WhyML, Viper, and Coq. This coexistence of multiple intermediate verification infrastructures allows the devised framework to target the verification of a large subset of OCaml programs, while combining the strengths of each individual intermediate language to obtain better verification results.

  • Open Access mandate for Publications
    Funder: EC Project Code: 896473
    Overall Budget: 184,708 EURFunder Contribution: 184,708 EUR
    Partners: BHL

    Methylene blue is the first fully synthetic drug used in medicine, the most effective and safe medicines needed in a health system. In addition, thioethers derivatives are important materials that are used in organic, bioorganic and medicinal chemistry and are also known to exhibit different biological activities such as antioxidant and antibacterial. These compounds are synthesized commercially by chemical methods that suffer from significant limitations, such as expensive and toxic reagents, solvents, tedious work-up, safety problems. Organic electrosynthesis is recognized as a typical environmentally friendly process with features that many of which cannot be achieved by other methods. Most electroorganic processes are performed under reagentless and mild conditions in one step using efficient and ecofriendly methods and are in agreement with all the principles of green chemistry. Within this field, the use of microreactors in continuous flow is also concurrent with electrochemistry because of its convenient advantages over batch, such as no supporting electrolyte at all, due to the small distance between electrodes; high electrode surface-to-reactor volume ratio, short residence time and etc. This project aims to fabricate an electrochemical flow microreactor by the novel method of photolithography to decrease the interelectrode gap below 100µm. Thus, the resulting device should be suited to the electrosynthesis of a wide range of reactions without a supporting electrolyte solution. Through the present project, we also aim electrochemical synthesis of methylene blue and some new thioethers derivatives for the first time with a facile one-pot and supporting electrolyte-free method. Overall, this method has shown to be a promising tool for electrosynthesis and improving the outcome of standard batch cells. As well as, during the whole of the project the ER will gain maximum knowledge in microfluidic integrated devices and benefit from entrepreneurship skills.

  • Open Access mandate for Publications
    Funder: EC Project Code: 953381
    Overall Budget: 3,145,120 EURFunder Contribution: 2,201,590 EUR

    Pollination is crucial to life on the planet. Bees and other pollinators have thrived for millions of years, ensuring food security and nutrition, and maintaining biodiversity and vibrant ecosystems for plants, humans and the bees themselves. Globally, 75% of crops producing vegetables, fruits and seeds for human consumption depend on pollinators for sustained production, yield, and quality. In recent years, most countries in the world have reported high rates of disorders affecting their honeybee colonies. The seemingly unpredictable loss of bee colonies exacerbates the shortage of pollinators, which reached an unprecedented global rate of ~30% compared to 2%-3% a couple of decades ago. The device beekeepers rely on to manage bees and take care of their ongoing upkeep is a wooden box designed 150 years ago, the beehive we’re all accustomed to seeing in the field. This “technology” does not allow beekeepers to maintain healthy bees in the face of modern challenges like pests, diseases, and climate change. Furthermore, this is the technology utilized to pollinate 75% of global crops for 7 billion humans, resulting in the most extreme pressure bees have ever experienced. Beewise developed the Beehome platform, which is a modular commercial AI-powered apiary composed of hardware and software that fully automates beekeeping while optimizing pollination and honey production. The technology is not exclusive to honeybees and can support various species of bees that face extinction as well. The platform includes an automated robotic brood box management system, a computer vision-based monitoring system, AI-based decision making, an automated honey harvesting system and systems for pest control, feeding, and thermoregulation. The key objectives of the project are to optimize the software and the AI, to finalize the engineering of the hardware components, to validate the technology in a two-stage in-field testing and to obtain the CE mark for commercialization in Europe.

  • Open Access mandate for Publications
    Funder: EC Project Code: 954040
    Overall Budget: 2,545,000 EURFunder Contribution: 1,781,500 EUR

    We developed TiiVii, a fully-automated, professional TV production platform, to help any sports club, league or federation to create their own scalable TV channels with live and on-demand content. At only 10% the cost of a traditionally-televised event, sport organizations will persuasively engage fans and commercial sponsors through interactive sport content. Our solution will create a new value chain that makes TV production available and affordable for non-premium sport segments, and their emerging content distributors - challenger telecom operators and publicly-financed local media broadcasters. Commercial TV sports production can cost up to €100K a game and 95% of European sports club competitions are never seen in a format accessible to their fans. Premium sports dominate all sponsor funding and media attention. The minority federations forfeit their digital media rights to more powerful parties to get any media exposure. Despite widely-connected mobile devices, sport fans have no access their favourite sports live. So far, the market has been applying single-stack artificial intelligence (AI) and ‘stitching’ of multiple camera video inputs. Niche sport codes are promoted with new video content but at no point does it satisfy the high-quality benchmark of professional TV production. The stitched stream with cropped sequences does not show 100% of what actually happens in the game. The result is a non-interactive, non-immersive stream that excludes the emerging technologies designed to support virtual reality and 3D experiences. We will progress TiiVii to a fully-automated production platform through a triple-AI-stack simulating a human production crew operating multi-camera rigs. We will build support for 8K cameras and implement 5G network interoperability to support instantaneous data exchange between sport venues, media distributors and content consumers. We will conduct B2B and B2C trials to validate TiiVii’s technology and business model.

  • Open Access mandate for Publications and Research data
    Funder: EC Project Code: 888322
    Overall Budget: 219,312 EURFunder Contribution: 219,312 EUR
    Partners: AU

    Cilia are essential hair-like structures presented at the surface of eukaryotic cells that allow motility, fluid flow and complex inter- and intracellular signalling events. Nine pairs of microtubules organized in a cylindrical shape called axoneme form the backbone of cilia. The formation and maintenance of cilia is dependent on a multi-subunit protein complex termed the intraflagellar transport (IFT) complex that actively delivers axonemal building blocks such as tubulin from the base to the tip of growing cilia. Lack of cilia or its miss-construction leads to severe developmental diseases called ciliopathies. Despite its fundamental role in cilium biogenesis, the process of tubulin recruitment, loading and unloading by the IFT machinery remains poorly understood. In this proposal, I aim to elucidate the mechanism of tubulin loading onto IFT complexes by determining high-resolution structures of intraflagellar transport (IFT) complexes bound to tubulin. Details about the IFT-tubulin interaction interface will be obtained by a combination of biochemical techniques like site directed photo- and chemical crosslinking followed by mass-spectrometry analysis and the structural biology techniques X-ray crystallography and single particle cryo-electron microscopy (cryo-EM). Ultimately, this study will enrich our understanding of cilium biogenesis and homeostasis by providing the first insight at atomic resolution into cargo selection and loading onto IFT machinery.

  • Open Access mandate for Publications
    Funder: EC Project Code: 954332
    Funder Contribution: 150,000 EUR
    Partners: Weizmann Institute of Science

    Very High Energy Electrons (VHEE) as those produced by compact laser plasma accelerators are ideal candidate in radiotherapy (RT). The corresponding dose distribution of the already produced low divergence and quasi-monoenergetic electron beam portends significant potential to treat deep tissue tumors, due to VHEE’s narrow radial dose deposition profile and long penetration distance. Our technological breakthrough is creating VHEE beam suitable for radiation therapy with a single laser and in relatively small space. Therefore, we expect our discovery to enable smaller, simpler and cheaper RT machinery with superior therapy performance. This will bring added value to RT device manufacturers and operators. Our approach substantially reduces the size of the acceleration complex leading to significantly smaller footprint, and investments in such facilities. We also enable increasing patient throughput while facilitating lower radiation protection requirements. The approach is safer for patients – for instance, our numerical studies of dose deposition in cases of prostate cancer indicate that VHEE reduces 20% of the ionizing radiation in healthy tissues. Moreover, obesity makes cancer treatment more difficult and adverse side effects more common, for which VHEE-RT represents an efficient and economically pertinent solution. In addition to increasing the technology maturity in this PoC, we will study and prepare commercialization plans of the approach and variety of VHEE-RT components. Moreover, we will carry out IP protection and networking tasks with collaborators, potential customers and investors for improving our chances of commercialization success.

  • Open Access mandate for Publications
    Funder: EC Project Code: 960401
    Overall Budget: 2,636,880 EURFunder Contribution: 1,845,810 EUR

    Advanced analytics and Machine Learning are disrupting the way organizations make business decisions. There are many different software products that focus on analysing images, videos, language and many more types of data. But one area that is still not developed is the analysis of location data, where things happen and why they happen there. To do market analysis, site selection and overall understand why things happen somewhere, you need a Spatial Analytics Platform and Location Data. Traditionally, the technology and the data have been produced and distributed by different organizations, making it hard for users to use them and especially hard for applying Machine Learning on them. With NextGen.DO GEO will develop a new paradigm of Location Data Marketplace connected to analytics technology that will reduce dramatically the time taken for spatial analysis and make it way more accessible. This requires harmonizing data from many providers using Machine Learning and building a common Index. We are looking at reducing the time it takes for a user to make use of a location dataset from 1 month to hours. With NextGen.DO, GEO will change the way location data is access, paid and used, and will result in substantial growth of GEO market penetration. GEO ambition is to become the world’s leading Location Intelligence platform, empowering organizations, with the help of third-party data streams and spatial analysis, to turn their location data into business outcomes. Our strategy is to create software and data products that will make Location Intelligence more widely accessible to every organization. With NextGen.DO, analysts, developers, and data scientists are equipped with the tools, APIs, and libraries needed to build Location Intelligence applications that can help businesses to make investment decisions, streamline operations, reduce costs, and much more.

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