Results 2022 CORE Call

The FNR is pleased to communicate the results of the 2022 CORE Call. Out of 174 eligible proposals submitted in the Call, a total of 47 research projects have been retained for funding (+1 pending decision from international partner), representing a financial commitment of around 31.3 MEUR.

CORE is the central funding programme of the FNR, with a prime objective to strengthen the scientific quality of Luxembourg’s public research in the country’s research priorities adopted by the Government on 20 December 2019. 

In order to identify the most promising and most excellent projects, the FNR submits project proposals to an assessment by independent international experts. Among the174  eligible project proposals that were submitted, 48 have been retained for funding. 

8 of the 48 projects are CORE Junior projects (CORE Junior PIs marked with * below). In the biomedical field, 2 projects pertaining to research relating to the National Cancer Plan are jointly funded by FNR and Fondation Cancer. 8 PIs are women, 40 are male.

FNR’s CORE programme is one of the major vehicles to implement the national research priorities. Funded research projects have a duration of 2-3 years and will be  implemented in Luxembourg’s research institutions. 

Find out more about CORE – 2023 deadline April

The retained projects of the CORE 2022 Call are grouped in the areas below.

Subcategory: Trusted data-driven economy and critical systems – 8 projects

Principal Investigator

Björn Ottersten

Project title

Metacognitive Radar For Emerging Sensing Applications (METSA)

Host institution

University of Luxembourg (SnT)

FNR Committed

€762,000

Abstract

Many of the recent scientific works in signal processing have been increasingly influenced by the most complex and least explored signal processing system – the human nervous system. Cognition refers to the process through which humans and animals sense and interact with their environment and cognitive radar signal processing aims to parallels to neurobiological cognition to learn from the sensed environment and act accordingly e.g., better focus the sensing on particular areas of interest while nulling others. While the radar gets data on the entire surrounding, it’s the cognitive signal processing that brings about the decision on how to act after inferring from the data.

Similarly, metacognition is a well-studied concept in both neurobiology and educational psychology, and can be termed as a higher order thinking which can be summarized as learning about learning or knowing about knowing. It is pertinent to remark the importance of metacognition as separate from plain cognition. Since the cognitive cycle is a closed loop system, without any provision of altering any of the steps once the cycle has kicked in a operational system. This leads to an inherent inflexibility of the system to adapt to drastic change in the channel conditions, change of engineering modules, or the operating objective or all of these. Hence, the radar must include multiple strategies with their own cognitive cycles. The selection of the appropriate strategy is handled by metacognition.

Consider the case of vehicles equipped with Automatic Emergency Braking (AEB) systems. It has been reported that many situations like bridges, railroad tracks and parking garages can trick the vehicles into breaking by making them believe that they are about to crash. Even steam coming out of underground tunnels and ducts in large cities can trigger the system, apparently. A standard operational cognitive radar cannot fully “learn” this situation. In a metacognitive radar, on the other hand, this flaw can be monitored and a learning strategy for this situation devised by selecting the optimization objective and solution. Furthermore, the learned information can be transferred in a connected networked so that other cars do not make the same mistake.

The project formalises such a learning for the different tasks of radar (detection, estimation, classification and tracking) with the transmit waveforms and receiver algorithms as the means of implementing the learned rules. The project aims to create a system that acts in optimal manner based on various possible strategies that can be learned from the environment.

Principal Investigator

Michail Papadakis

Project title

Metamorphic Relation Inference Automation (MeMoRIA)

Host institution

University of Luxembourg (SnT)

FNR Committed

€939,000

Abstract

Software Testing forms one of the key quality assurance methods and is a vital ingredient of the modern software development practices. Deciding if a program execution corresponds to a correct/incorrect behaviour is currently a manual task. To this end, MeMoRIA will automatically generate a set of (metamorphic) properties that distinguishes good from bad software behaviours. Hence, MeMoRIA aims at investigating and solving this real-world industry relevant problem, and contributing with the adoption of automated testing.

Principal Investigator

Ehsan Ebrahimi*

Project title

Quantum Safe Proofs (QSP)

Host institution

University of Luxembourg

FNR Committed

€521,000

Abstract

Currently, there are a lot of investments and research to build a full-scale quantum computer. Advances in this realm have two drastically different impacts: 1) Positive: The way a quantum computer doing computations is fundamentally different from a classical computer and this will help to solve some problems that are intractable for a classical computer and to open up new technological applications and opportunities. 2) Negative: A full-scale quantum computer can be used to attack classical cryptographic constructions. This compromises the security and privacy of our digital communication.

A proof (argument) system is a cryptographic protocol that will be affected negatively by a quantum hacker. To illustrate a proof (argument) system, let say one wants to prove that she/he possesses a password to log in to an online bank account without revealing her/his password. This task can be done by a proof (argument) system. Considering many real-world applications of succinct proofs, e.g. electronic voting systems and cryptocurrencies, it is essential to investigate the effect of a quantum adversary to the proof (argument) systems. In case of a security break, it is necessary to develop proof (argument) systems secure against a quantum hacker. In this project, we conduct this investigation and will develop quantum secure proof (argument) systems. Beside the scientific contribution of our project, we expect a post-quantum secure cash system as an output of the project. In addition, our result can be used in any application that uses a proof (argument) systems as a building block to guarantee the (post-) quantum security.

Principal Investigator

Bhavani Shankar Mysore Rama Rao

Project title

Signal Processing For Sensing Using Intelligent Surfaces (S3)

Host institution

University of Luxembourg (SnT)

FNR Committed

€892,000

Abstract

Proliferation of radar sensing in novel applications imposes stringent requirements on performance while exploiting only a limited number of resources and with a limited amount of power. Further, the scenarios being considered are dynamic requiring the systems to be flexible and be adaptable with negligible or no human intervention. For example, indoor sensing require detailed information about the interiors, separating the different closely objects, irrespective of the lighting conditions while having constraints on placement, number of sensors and potential interference to mobile communications. Further, the scenarios are dynamic, with the number of objects and people varying in number, orientation etc. The radar systems need to distinguish between different closely spaced objects, recognize the number, posture, orientation without the semantic information made available by a camera. While radar sensing offers a cost-effective and small form-factor solution, current technology needs to be improves to offer the required performance and flexibility. Delving deeper, the radar system comprises of the Radio Frequency (analogue) components and digital processing. Traditionally, the digital processing offers flexibility exploiting the available information, while the radio frequency parts are kept fixed. To enable the radar systems to meet the earlier said demands, a synergetic adaptation of the digital processing and the radio frequency parts are mandated. In this context, in addition to the advances in digital radar signal processing, reconfigurability of the Radio Frequency (analogue) components offers additional degrees of freedom to overcome the shortcomings of radar.

Thus far, the radar systems had Radio Frequency components separate from the digital processing. Integrated chipsets incorporating the key analogue processing and antennas together with digital processing are being increasingly considered for the newer bands to be used for sensing and communications. The use of novel materials for such chipsets, known as metamaterials, enable the reconfigurability of analogue components at low-cost and low power. The properties of these metamaterials can be controlled rendering their intelligent operation in a manner required by the application. This project considers the use of such intelligent surfaces for radar sensing, addresses the challenges of their incorporation (handling flexibility needs to be aced as in other fields) and demonstrate the gains for indoor imaging and monitoring. The project also aims to validate the gains through in-lab activities lending the project outcomes closer to reality.

Principal Investigator

Peter Y. A. Ryan

CORE Bilateral: NCBR

Project title

Probabilistic Verification Of Complex Heterogeneous Systems: From Ballots To Ballistics (SpaceVote)

Host institution

University of Luxembourg (SnT)

FNR Committed

€639,000

Abstract

In the last 30 years, the world has become densely connected. Most ICT systems address a complicated network of users, vastly distributed over geographical locations and cultural contexts. What is more, ICT services are usually done by people, with people, and for people. The intensive human involvement makes them hard to describe and analyse with the standard tools of formal verification.

Voting and elections are good examples of services that are difficult to specify, hard to verify, and extremely important to the society. The democratic societies are currently facing a number of serious threats. Electoral fraud, manipulation of voters, fake news and disinformation are used to swing the outcome of elections and severely undermine the voters’ trust. If democracy is to be effective, it is essential to assess and mitigate those threats. In the course of our previous projects, we have used ideas from game theory, multi-agent systems, and theory of socio-technical systems towards the goal, with considerable success. It is now time to move on to richer formalizations that allow for reasoning about more realistic models of voters and attackers, and more mathematical analysis of their possible behaviour. To this end, we will extend our techniques to quantitative analysis of voting, and combine them with the recent advances in probabilistic verification.

We will also show that the methodology can be applied well beyond voting procedures, for example to better synthesize strategies for small autonomous rockets navigating in an uncertain environment.

Principal Investigator

Sjouke Mauw

Project title

Automated Verification Of Privacy In Electronic Voting For Strong Adversaries (AVVA)

Host institution

University of Luxembourg

FNR Committed

€414,000

Abstract

As more activities are performed online, many of them related to government services, there are expectations that elections should follow the trend. In recent years, governments in conjunction with the industry started running pilots to asses the feasibility and security of electronic voting, some prominent examples being in Norway, Estonia and Switzerland. In fact, internet voting is already used in the real world for elections with relatively lower stakes than political elections, e.g. for memberships in international organisations and leadership positions in universities. However, secure electronic voting is a more difficult problem than, say, secure online banking or secure messaging. In addition to external attackers and network threats, electronic voting is subject to threats from parties and infrastructure running the election: e.g. voting platforms and servers, parties responsible for voter registration, parties collecting or tallying the ballots, etc. The adversary may also coerce voters, or be a powerful state actor investing significant resources towards interfering in another country’s election process.

Considering this complex threat landscape, we need systematic methods to ensure future electronic voting systems are indeed secure. We need to reason in advance about all possible attacker actions and rigorously conclude whether a desired property is satisfied or not. Automated tool support is an essential element in this task. The main goal of our project is to develop methods that allow realistic, rigorous and automated formal verification of security for electronic voting protocols, with a focus on vote privacy. We will address several challenges related to this objective: we will develop precise specifications for the properties that we want to achieve, for the protocols implementing them, and for the possible actions of the adversary. Furthermore, we will also develop techniques that improve automated verification such that we can have high assurance automated guarantees of security for electronic voting systems.

Principal Investigator

Domenico Bianculli

Project title

Automated Log Smell Detection And Removal (LOGODOR)

Host institution

University of Luxembourg (SnT)

FNR Committed

€678,000

Abstract

Logs are special text files produced by computing systems: you can find them on your mobile phone, on your laptop, and on large enterprise information systems. They are used by software developers to record important events of applications and of the computer, such as the arrival of a network message, the change of a setting, or an unexpected situation (like an error). Logs are also used by special type of programs – called log-driven analyses – to assure the reliability of the computing system, for example to detect an anomaly in the system.
The effectiveness and the efficiency of log-driven analyses depend on the quality of the logs, which can be summarized as the level of information about the system execution contained in a log. This quality attribute depends on the way developers have written the code producing the information recorded in the logs, which we call the “logging code”. Unfortunately, developers can make mistakes when programming (for example, because they have to quickly release a new version of an application) or can neglect to update the logging code when they change other parts of an application. As a result, the logging code is not aligned anymore with the core functionality, leading to low-quality logging code that produces low-quality logs.

To address the above issue, LOGODOR will leverage the concept of “smells” (as in “code smells”). In the same way “code smells” represent any characteristic in the source code of a program that possibly indicates a deeper problem, we will define the novel notion of “log smells””, i.e., any characteristic in the logs of a system that possibly indicate a deeper problem related to logging. The notion of log smells introduced by LOGODOR will cover both code-level log smells, i.e., smells specific to the logging code, and message-level log smells, i.e., smells related to the log messages and their textual content.

Based on the notion of log smells, LOGODOR aims to develop automated and scalable approaches for detecting and removing a wide range of log smells, by focusing on four specific activities: (1) development of a comprehensive catalogue of log smells, (2) automated detection and removal of code-level log smells by enhancing the logging code, (3) automated detection and removal (or mitigation) of message-level log smells by cleaning log messages when accessing the logging code is not feasible or possible, and (4) evaluation of the developed techniques and tools in terms of their effectiveness, efficiency, and benefits.

Principal Investigator

Tomer Libal*

CORE Bilateral: NCBR

Project title

Examples Based Ai Legal Guidance (ExAILe)

Host institution

University of Luxembourg

FNR Committed

€401,000

Abstract

Being compliant with regulations in general, and the GDPR in particular, is required from almost all companies. Nevertheless, the legal language itself is usually complex and requires the intervention of legal experts. This problem has prevented AI from being used efficiently to help solving such compliance issues in applications intended for non-legal experts. The objective of the research is to simplify the access to the legal knowledge via an artificial intelligence system, able to explain abstract legal concepts with easy to understand examples. Let us consider the problem of digital marketing in the context of GDPR. The regulation makes references to the concept of legitimate interest, yet a person running a small company may struggle understanding what does it mean, to have a legitimate interest. The proposed solution, guides the user in their journey towards compliance, but at the same time, uses state-of-the-art artificial intelligence in order to explain the legal concepts via relevant examples.

Subcategory: Integrative materials science and technology – 11 projects

Principal Investigator

Adolfo Del Campo Echevarria

Project title

Adiabatic Quantum Computation With Ising Quantum Networks (AQCQNET)

Host institution

University of Luxembourg

FNR Committed

€632,000

Abstract

Emergent quantum technologies such as quantum computation have a unique potential for industrial and service transformation. Their commercialization has already had a major impact on higher education, research, and academia. A particularly advanced form is that of adiabatic quantum computation that relies on quantum annealing. It provides a way of solving complex optimization problems. Its applications are manifold and include portfolio optimization, forecasting election polls, prediction of financial crashes, the evolution of financial derivatives, optimization of investment, image acquisition, traffic flow, and nurse scheduling, among others. For example, several major banks have started exploring quantum optimization in their business model. Devices performing quantum annealing are available in laboratories across the world and have been commercialized by companies such as D-Wave. Cloud quantum computing facilities online such as those created by IBM can also be applied to quantum annealing. Deepening the understanding of quantum annealing as a physical nonequilibrium process is fundamental to further advance this technology. AQCQNET aims at achieving this goal by combining tools of network theory, quantum many-body physics, and nonequilibrium scaling theory. The project Central to quantum annealing is the mapping of the optimization problem to that of finding the lowest energy configuration of a physical system with many discrete degrees of freedom known as spins. The interactions between spins can be described as a graph and characterized using the tools of network theory. AQCQNET aims at relating the performance of quantum annealing to solve optimization problems with the underlying network topology of the interacting spins in which the problem is encoded. By doing so, it aims at introducing novel algorithms for quantum annealing using local protocols exploiting the network topology. By benchmarking their performance against classical methods, AQCQNET aims at identifying scenarios in which the quantum properties provide an advantage. Overall, the project focuses on fundamental phenomena defining the functioning and performance of devices for quantum computing and quantum technologies.

Principal Investigator

Adolfo Del Campo Echevarria

Project title

Universal Distributions Of Topological Defects: Beyond The Kibble-zurek Mechanism (BeyondKZM)

Host institution

University of Luxembourg

FNR Committed

€632,000

Abstract

Most materials in nature exhibit phase transitions between different phases of matter. Water can be found in ice, liquid, or vapor form. A piece of iron can acquire or loss its magnetic properties as a function of temperature. Understanding the dynamics across phase transitions is crucial for many applications ranging from the exploration of novel materials to quantum computation. Even when a material is driven slowly across a phase transition, excitations appear in it. Indeed, the crossing of so-called continuous phase transitions results in topological defects, a kind of excitation that is particularly robust and stable. As a result, topological defects govern many of the physical properties of a given phase of matter. For example, the observation of vortices can inform about the superfluid or superconducting character of a given sample. Topological defects in solids can seed cracks leading to material failure. In addition, topological defects shed new light on the fundamental laws of physics such as the occurrence of the Higgs mechanism, the study of which was recognized by the Nobel Prize.

A theory known as the Kibble-Zurek mechanism (KZM) predicts that the density of topological defects created in the course of a phase transition follows a universal law, increasing with the rate at which the transition is crossed. The KZM formula governing this increase can be calculated using solely the equilibrium properties of a system, providing a precious bridge between in and out of equilibrium phenomena. Moreover, such behavior is shared by many materials alike, grouped in so-called universality classes, making the results universal and of broad applicability. Since its conception by Kibble and Zurek, the KZM has been the subject of intense study sustained over decades of research. It was first explored in a cosmological setting and has by now been applied to colloids, liquid crystals, superfluids, superconductors, multiferroics, and many other materials.

However, findings to date have been focused on the characterization of the mean density and quantities depending upon it. The Project BeyondKZM aims at providing a paradigm shift, by opening a new research focus on the statistical properties of topological defects generated across phase transitions. The working hypothesis, motivated by preliminary findings, is that not only the density of topological defects is universal, but the fluctuations governing the distribution of the number of topological defects and their location are also universal. A crucial lesson from twentieth-century physics is that many phenomena are not dictated by average properties but are governed instead by fluctuations. The Project “BeyondKZM” aims at exploring and describing such new physics by combining two disparate fields of research, namely, the theory of phase transition dynamics (KZM) and a branch of mathematics dealing with random processes. In doing so, Physics unveiled by the project BeyondKZM will be directly applicable to the plethora of systems in which topological defects can be imaged. We thus expect this project to motivate a new generation of experiments. Overall, this project will advance the frontiers of nonequilibrium phenomena and the prediction of material properties governed by topological defects.”

Principal Investigator

Carlos Fuentes Rojas*

CORE Bilateral: FWO

Project title

Bio-inspired Design Of Fibre Interfaces With Intermittent Weak And Strong Areas For Obtaining Tough Composit (BioInter)

Host institution

Luxembourg Institute of Science and Technology (LIST)

FNR Committed

€676,000

Abstract

One of the most ambitious goals in structural materials is to achieve exceptional mechanical properties, with an ideal combination of light weight, high strength, and high toughness.For many biomaterials, strategies to achieve the advantageous unification between structure and mechanical properties have been through millions of years of evolution, as in the case of nacre, one good example of a material that combines high strength, high stiffness, and high toughness. Inspired by nature strategies to increase toughness, BioInter proposes to engineer the interface of composites by creating alternate sections around the fibre and along the fibre length of high and low adhesion with the matrix using micro-plasma surface deposition and activation, promoting intermittent sections of high and low shear strength during the process of debonding. The strong regions ensure that the filament strength is taken, while the weak areas weaken the running crack, creating a complex pattern for crack evolution.

Principal Investigator

Ludger Wirtz

Project title

Exciton-phonon Coupling In Luminescence Of Materials With Indirect Band Gap (ExcPhon)

Host institution

University of Luxembourg

FNR Committed

€526,000

Abstract

Optical spectroscopy (light absorption and light emission) is an important method to gain information about the microscopic structure of materials. The link between experimental data and a full understanding of the atomic structure of a material is usually made via theoretical calculations. The development of computational methods for the description of the complex optical properties of materials is thus an important ingredient for the characterization and the design of novel materials with tailored optical properties. These calculations are by now rather standard for materials with direct band gap where a photon (light particle) can be directly absorbed or emitted. However, for the large class of materials with indirect band gap, where photon absorption or emission is accompanied by excitation of lattice vibrations (phonons), a reliable and efficient calculation method is still missing. We will address in particular the class of layered materials and single-layer 2D materials, where strong excitonic effects (states where the excited electron in the conduction band is bound to the hole left behind in the valence band) are often occurring. The combination of strong excitonic effects and indirect band gaps requires the development of a new computational approach where absorption and emission of photons is coupled to the excitation of lattice vibrations (phonons). In this project, we will develop the methodology and implement it in an efficient computer code. We will study some seemingly simple prototype materials (such as diamond and hexagonal boron nitride) where the luminescence spectra contain complex features that are still not understood. The final goal is to calculate phonon-assisted optical spectra routinely of a large number of materials in an automatized (“high-throughput”) way, creating a reliable data base of optical properties of materials.

Principal Investigator

Susanne Siebentritt

Project title

Fundamental Limitations Of Thin Film Solar Cell Efficiencies (FULL)

Host institution

University of Luxembourg

FNR Committed

€769,000

Abstract

The law of physics pose certain limitations to the efficiency of solar cells. The efficiency of a solar cell is the share of solar energy falling on the cell that is transformed into electricity. For example the laws of thermodynamics limit the efficiency of a single solar cell to about 33%. Just for completeness: combining different solar cells in tandem cells or multi-junction solar cells allows to overcome this limit. The best solar cell so far has an efficiency of more than 47%.

These limitations are well understood for ideal solar cells. However in real solar cells many more limitation appear. Some of them can be overcome by optimisation. Other are more fundamental and due to the very nature of the structures and materials used in the solar cell.

Accepted models exist to describe these fundamental limitations of real solar cells. However, they have only partially been checked experimentally. In this project we aim to check these models fully experimentally and to understand better which limitations are fundamental and how the different aspects of solar cell design interact with each other.

This endeavor will allow us to define new design rules for solar cells and to improve them.

Principal Investigator

Tirthankar Banerjee*

Project title

Stochastic Thermodynamics Of Active Turbulence: From Quantifying Dissipation To Modelling Active Engines (ActiveTurbulence)

Host institution

University of Luxembourg

FNR Committed

€417,000

Abstract

Non-equilibrium physics in general owes a lot to the fascinating phenomenon of fluid turbulence. Both the natural and artificial worlds are full of examples of how turbulence plays a significant role in our lives, ranging from small and large-scale climate effects, mixing of dyes in solvents, to aerodynamics of cars and jet engines, to name a few. Fluid turbulence has traditionally sat at the interdisciplinary junction of fluid dynamics and statistical mechanics, where statistical properties of fluid flow are studied under the applications of external drive.

Fluid Turbulence has many intriguing properties: for example, the symmetry breaking at small length scales (close to boundaries), only to be restored once again at large length scales, away from boundaries; or the self-similarity of flows across length scales. These and other interesting phenomena associated with fluid turbulence remained the core of non-equilibrium physics until a couple of decades ago, when studies on ”active matter’ exploded onto the research scene. Usually active matter refers to ‘self-sustained’ flows, where the systems spontaneously take-in and dissipate energy to and from their surroundings for their mechanical motion. Examples include naturally occurring bacteria or sperm swarms, and even artificial counterparts, such as Janus particles. State of the art non-equilibrium physics aims to answer one question : Can we understand fundamental principles of life through a statistical physics approach? It is in this context that the discovery of turbulent-like flows in such living and active systems some years back, led to the creation of the field of ‘Active Turbulence’, which deals with characterizing features of turbulence for active systems. Our CORE-junior project fits exactly to this theme.

Our aim is two-fold: We are proposing a novel theoretical approach for characterizing universal properties of Active Turbulence , and thereby exploiting such models to quantify the associated energy dissipation in order to design efficient active engines. The study of engines lies at the heart of equilibrium thermodynamics. It is imperative now that ideas such as power fluctuations and efficiency are considered for stochastic active processes, to lead to a fundamental understanding of non-equilibrium physics in general. We propose to use analytical and numerical techniques which have proved to be very successful in studies of turbulence of passive systems, and expect our new results to be verifiable in experiments on bio-physical systems.

Principal Investigator

Alexandros Gerakis

Project title

Velocity Distribution Function Shaping Of Ions With Intense Optical Lattice (VERITAS)

Host institution

Luxembourg Institute of Science and Technology (LIST)

FNR Committed

€672,000

Abstract

The VERITAS project is about using lasers, which are high power light beams, in a specific configuration for the manipulation of motion of charged particles (ions). Due to this light-matter interaction, it is possible to create different phenomena: These particles can for example be accelerated by the lasers so that they achieve higher velocities. On the other hand, deceleration of the particles by the use of the lasers can also be achieved so that the particles are slowed down to a standstill. A third type of interaction that can envisioned is that a group of ions having an initially large range of velocities, after interacting with the specially structured laser light, can be brought down to a smaller range of velocities, leading towards all ions having only one single velocity in the end.

All of these aspects will provide scientists novel ways to precisely handle charged particles and will lead to numerous improvements for existing scientific and industrial instruments. For example, it will be possible to perform microscopy imaging of smaller material features with even higher resolution, revealing more details about the structure of these materials. Furthermore, studies about the chemical composition of materials will be improved in order to understand even better of what these materials are made of at a smaller scale.

In general, these achieved instrumental optimisations will lead to a globally better understanding and characterization of materials involved in various relevant technologies of today. For example, the functionality of solar panels, batteries, fuel cells or other electronic devices can in this way be even better understood and improved. This will lead at long term to a reduced power consumption of electronic devices, improve the production efficiency of renewable energy devices or lead to more sustainable solutions during the production phase of these devices. Hence, the VERITAS project can at the end have a considerable impact on energy and environmental related topics, having therefore an immediate impact on the society of tomorrow.

Principal Investigator

Aritra Kundu*

Project title

Non-diffusive Fluctuations

Host institution

University of Luxembourg

FNR Committed

€409,000

Abstract

Non-diffusive fluctuations are ubiquitous in nature and provide a crucial link to unravelling new dynamical phenomena. They have deep consequences in various aspects of physics, biology and engineering. For example, non-diffusive fluctuations explain how the thermal conductivity at nanoscale systems is enhanced or the birds optimise resources when non-diffusively foraging for food. The project aims at understanding analytically tractable microscopic classical and quantum models which shows non-diffusive behaviour. WP1 and WP2 relate to the study of non-diffusive heat fluctuation in classical many-body systems in the interdisciplinary aspects of the stochastic process and Hamiltonian systems which are externally driven. In WP3 we will extend the analysis to the quantum system being randomly driven which characterises the dynamic fluctuations of energy in the heating dynamics of the system. In summary, the project will improve our understanding of non-diffusive dynamical fluctuations arising in classical and quantum systems. The project will add to the knowledge in specific cases for the question of the microscopic origin of non-diffusive fluctuations and a relevant macroscopic framework using hydrodynamics or fractional operators to describe it.

Principal Investigator

Daniel Schmidt

CORE Bilateral: South-Tyrol

Project title

Vitrimer-based Sustainable Flexible Electronics (V-Safe)

Host institution

Luxembourg Institute of Science and Technology (LIST)

FNR Committed

€676,000

Abstract

Electronics are everywhere, from our cars to our kitchens – and unfortunately, electronic waste (e-waste) is as well. 53.6 million tons was produced worldwide in 2019, up 21% from 2014, and 74 million tons is predicted to be produced by 2030. This has substantial environmental and health consequences, especially since so much of what is made is not recycled or recovered. A typical printed circuit board is mostly made up of glass-fiber reinforced epoxy resin – a three dimensional network of large molecules linked to one another irreversibly via strong chemical bonds. Such materials are extremely robust and perform well, but they are often composed of compounds that are non-renewable, harmful and/or persistent, a problem exacerbated by the fact that they cannot be melted or dissolved making recycling impossible. Instead, they are typically incinerated or landfilled, which can lead to the release of harmful compounds and cause harm to human health and the environment.

With this as the backdrop, we continue to witness increasing levels of functionality and performance when it comes to electronics, with one of the most recent developments being flexible systems. To emphasize how fast things move, the first foldable smartphone was demonstrated in 2006. The first commercially available model hit the market in 2018, and by 2021, 7.1 million units were shipped (up 264% from 2020). While this constitutes only a small fraction of the total smartphone market, this brief history highlights the growth of flexible electronics. If things are not done differently, such growth will not only lead to amazing new devices, but also to significant amounts of additional e-waste.

This project aims to address these issues by demonstrating the possibility to integrate two highly complementary technologies: flexible transient electronics and vitrimer networks. The materials that make up flexible devices (conductors, semiconductors and insulators) are carefully formulated and selected such that, in contrast with their conventional analogs, they can be efficiently dissolved in minimally harmful media (e.g. water, aqueous solutions, low-hazard organic solvents). Vitrimers are three dimensional networks of large molecules linked to one another by chemical bonds, but with a twist: these chemical bonds are strong and stable when the materials are in use, but when they are heated above their use temperatures, these same bonds become dynamic, mobile and reactive – allowing us to reuse, repair, recycle and recover these materials in ways that were formerly impossible with such networks. Given strong experience in both areas, our teams at the University of Bozen-Bolzano (UniBz) (South Tyrol, Italy) and the Luxembourg Institute of Science and Technology (LIST) (Luxembourg) aim to combine these technologies to produce next generation flexible electronics that are designed not only with performance in mind, but with the end-of-life accounted for as well. In this way, we avoid the generation of new e-waste in favor of a future where such systems are designed with greater sustainability for ourselves and our environment.

Principal Investigator

Project title

Detecting Quantum Skyrmions (DeQuSky)

Host institution

University of Luxembourg

FNR Committed

€633,000

Abstract

Skyrmions are localized magnetic vortices in ferromagnetic materials. Their properties have been the subject of intense investigation over the past decade, mainly thanks to their potential use in next-generation magnetic storage devices.

Typical skyrmion sizes are between nanometers and micrometers. However, at the smallest length scales, quantum effects should be taken into account. Indeed, recent years have witnessed a growing interest in the quantum-mechanical properties of skyrmions.

In this project, we will therefore investigate skyrmions in the quantum regime. We will study suitable quantum-mechanical model systems using a combination of numerical and analytical approaches, which will allow us to obtain a comprehensive theory of skyrmions ranging from the quantum regime to the classical regime. Moreover, classical continuum calculations will serve as a gauge to the quantum calculations. We will use this to calculate experimentally observable quantities, such as the spin structure factor, which can be determined in neutron-scattering experiments. Hence, our project will propose materials for the existence of quantum skyrmions, study their unique quantum-mechanical properties, and propose ways to detect them experimentally.

Principal Investigator

Project title

Protein Field Effect Transistor Sequencing (PROFET-SEQ)

Host institution

Luxembourg Institute of Science and Technology (LIST)

FNR Committed

€779,000

Abstract

DNA and proteins are the molecules that rule life. Reading their sequential composition has allowed us to understand their role in life to tackle health issues and make new products based on natural components that have become commodities of modern life.

Specifically, DNA sequencing has allowed the irruption of new medicines like the development of RNA vaccines or the new personalised therapies based in genetics.

Meanwhile, proteomics is lagging behind because the methods to “read” the composition of proteins are still cumbersome, expensive and require too many molecules compared to DNA sequencing. However, proteins are the real architects of life, thus, many prospect applications in precision medicines and protein engineering for green industries demand improving the performance of protein analyses while working with fewer molecules, increasing the throughput and at a lower costs.

In this project we approach this need with a new design of a lab on a chip technology that uses a novel electrochemical methods to disassemble the proteins in an ordered array of sensitive sensors. The constituent amino acids become immobilised into very reactive sensors that detect their fingerprints employing very few molecules to reconstruct the protein sequence.

This technology works with minimum amounts of samples and uses electronic components that can be mass produced at low costs to democratise the access to protein sequencing.

Subcategory: Future computer and communication systems – 2 projects

Principal Investigator

Pascal Bouvry

CORE Bilateral: NCBR

Project title

Space Data Brokering Optimization System (SERENITY)

Host institution

University of Luxembourg (SnT)

FNR Committed

€517,000

Abstract

The Global Navigation Satellite System and Earth Observation market had revenues of around €200 billion in 2021 and is expected to reach €500 billion by 2031. Many satellites from different vendors are carrying out their work in space. Additionally, all the data they acquire (images, recordings, analysis, raw data, etc.) may be offered by different providers. The huge amount of collected data requires appropriate storage, classification, and further processing for final use. Data lakes are the place where any data can be stored. The relative initial maturity of this market shows many aspects that can be dramatically improved to achieve much better end benefits – and for all parties to the transaction.

In the current context, many customers might be interested in combining data of two or more satellite data providers, e.g., to obtain more frequent data or to merge data of several types. To this end, the customer needs to request data separately from each provider. Such a scenario is sub-optimal since it requires the customer to know the different providers. A data marketplace is one promising solution for this problem. It is an online platform where users can sell or buy data from different sources.

The SpacE data bRokEriNg optImizaTion sYstem (SERENITY) project, aims to propose a novel type of marketplace where space data providers and consumers interact through a data broker that relies on a data lake storage. To this end, the SERENITY project will develop novel artificial intelligence and data storage approaches that will permit to tackle objectives like maximising providers’ profits, optimising data latency and minimising total purchase cost for customers.

Principal Investigator

Thang Xuan Vu*

Project title

Distributed And Risk-aware Multi-agent Reinforcement Learning For Resources And Control Management In Multilayer Ground-air-space Networks (RUTINE)

Host institution

University of Luxembourg (SnT)

FNR Committed

€696,000

Abstract

The beyond 5G (B5G) networks are designed to serve both human-oriented services, e.g., 4K video streaming and augmented reality, and cyber and machine-type applications, e.g., smart cities, automotive and industrial IoTs. These different and sometime conflicting QoS requirements from vertical services, e.g., ultra-high data rate and stringent latency constraints, pose unprecedented challenges in B5G network design and optimization under limited bandwidth and power resources. To tackle these challenges in addition to enhancing ubiquitous coverage, B5G systems are built upon multi-layer ground-air-space network architecture to efficiently harness the spatial densification along with advanced PHY signal transmission techniques. The multi-layer architecture, in one hand, provides the agility and flexibility in meeting diverse QoSs from heterogeneous services, on the other hand, extremely increases the system dynamics and complexity. Conventional model-based methods seem unfortunately insufficient to cope with such stringent requirements and sheer complexity of B5G, which is mainly due to i) lack of precise modelling for highly complex and heterogeneous systems and ii) limited time to obtain the system-wise state information as well as the real-time optimum solution.
In this project, we investigate the data-driven paradigm for B5G design and optimization by proposing novel risk-aware and distributed DRL-based resource management to overcome the limitations of the conventional RL in the B5G context. One key issue is how to determine and present the risk factor in the learning model to simultaneously accelerate the learning performance and minimize the chance of violating the QoS. Although there exist risk-aware RL in the literature, they evaluate the risk by the universal metric as the variance of the reward function, which ignores the inherent network topology and the eventual goal of the tasks.

Subcategory: Space telecommunications, earth observation and space resources – 1 project

Principal Investigator

Andreas Makoto Hein

Co-PI: Maxime Cordy

Project title

Space Data Brokering Optimization System (SAMP)

Host institution

University of Luxembourg (SnT)

FNR Committed

€842,000

Abstract

Luxembourg has been successful in creating in a very short time, a space ecosystem with over 60 startups, addressing diverse short-term to long-term business cases. This has positioned Luxembourg as a global hotspot for established and emerging actors from the international space economy such as iSpace, Redwire, Bradford Space, etc.

However, an architecture (high-level design) of Luxembourg’s space program is currently missing, which describes which space missions are conducted in which order and which space systems, technologies, and actors exist, will exist, or should be developed. A space program architecture is a high-level description of a space program. It would support steering the strategy of the Luxembourg space ecosystem but also guiding companies where to position themselves within that ecosystem. While a high-level space roadmap exists for Luxembourg, it is rather schematic and does not provide much detail on how the underlying actors, technologies, space missions, and their sequencing are linked to address key economic and societal factors.

A space program in the following is understood as a combination of top-level strategic goals with lower-level combinations of space missions, hardware, and technology. A space program goes beyond an individual space mission (e.g. an Earth observation satellite mission) and usually combines multiple missions in a sequence along with the used systems and technologies. It links strategic objectives (political, economic, societal, environmental, etc.), which are usually high-level (often national) with means to achieve them (systems, technologies, etc.).
Representing a single mission is complex but has been treated in the existing literature abundantly. However, the sequencing of missions in time, with respect to the underlying systems and availability of technologies in an ecosystem is much more complex but has great strategic value in supporting the decision-making process of key stakeholders such as the Luxembourg Space Agency and various ministries (Ministry of Economy and Ministry of Defense).

Designing a space program is a highly collaborative activity, bringing together diverse stakeholders and a key benefit lies in developing a shared understanding during the process. Contrary to traditional space program architectures which are paper-based, recent advances in this field and in technology roadmapping indicate that a model-based approach to defining space program architectures seems to be promising. Instead of a textual document, a model of the space program architecture allows to integrate and link diverse data and to run simulations to analyze the impact of one or multiple space program architectures. Such a model-based approach enables to design and evaluate space program architectures during workshops with stakeholders, analyzing the impact of changes (political changes, technological changes, etc.) and opens the door to a more thorough approach to strategic decision-making, also in domains beyond space, e.g. energy, mobility, healthcare.

How can a space program architecture be collaboratively designed, which integrates strategic goals, technologies, space missions, actors, etc. in order to facilitate decision-making?
SAMP will address the above research question by proposing a number of computer models and approaches that will allow decision-makers (e.g. engineers and managers from industry, government officials, representatives of local communities) to collaboratively design a space program architecture.

These expected outputs will support decision-makers and stakeholders to explore different space program options and the potential impact of changes to the program and with respect to external, e.g. political events. The method presented in SAMP will provide a basis on which future methods for other domains such as healthcare, energy, and mobility could be based, supporting strategic decision-making.

Subcategory: Autonomous and intelligent systems and robotics for earth and space – 3 projects

Principal Investigator

Jose-luis Sanchez-lopez*

Project title

Deep Understanding Of The Situation For Robots (DEUS)

Host institution

University of Luxembourg (SnT)

FNR Committed

€495,000

Abstract

Robotics is considered the Holy Grail that has promised to change the world as we currently know it, becoming a central part of our lives in a fully robotized society. Service robots assist humans at work in non-industrial settings or in the home, needing to operate in complex dynamic unstructured environments. Robots need to continuously acquire a complete situational awareness, by perceiving the environment within time and space, comprehending its meaning, and projecting it in the future, to enable intelligent decision-making and autonomous tasks execution.

The project DEUS (which means God in Latin), focuses on the development of a novel robotic situational awareness as it is an essential missing CORE capability on autonomous and intelligent robots which is blocking their further development. We will provide the robots with an understanding of the situation with multiple levels of abstraction such as geometric (e.g. shape of the objects), semantic (e.g. type of the objects), or relational (e.g. relationships between the objects). This understanding will not be limited to the current situation (i.e. what is the situation that the robot perceives at the present moment), but it will create a long-term situational understanding (i.e. what is going on around the robot) by integrating the perceived measurements from multiple sensor sources with past observations and background knowledge.

We will develop a robotic situational awareness by combining adapted versions of novel machine learning based techniques with extended versions of traditional optimization based algorithms, to get the best out of each of them. Our research will focus on two different aspects. On the first hand, we will research how to acquire a deep long-term situational understanding from the sensor measurements. On the other hand, we will focus on the acquisition of semantic-relational situational understanding by reasoning on the knowledge that the robot previously acquired.

Our research will be experimentally validated using our ready-to-use robotic platforms and we will prove its technological relevance by demonstrating a proof-of-concept in two real-world use-cases we have selected, namely a UAS for surveillance of critical infrastructure, and a walking robot for inspection of construction sites.

Our expected open access publications, our datasets and one PhD thesis will generate high scientific impact. We also expect that the DEUS project will bring high long-term socio-economical impact, by providing the foundations of an essential component of the robotic artificial intelligence that will enable a limitless number of potential applications for service robots.

Principal Investigator

Holger Voos

Co-PI: Jan Lagerwall

Project title

Control Of A Soft Aerial Manipulator With Clce-based Optical Strain Sensing (COSAMOS)

Host institution

University of Luxembourg (SnT)

FNR Committed

€796,000

Abstract

While Unmanned Aerial Vehicles (UAVs) were initially applied as flying sensors, recent years have also seen a rapidly increasing interest in Aerial Manipulators (AM) by attaching a robotic arm and gripper to a UAV. AMs dramatically increase the spectrum of UAV applications, but especially the use of rigid manipulators is difficult: they are safety-critical especially when interacting with humans, difficult to control and have problems when gripping of irregular shaped or unknown objects is required. In order to cope with these challenges, there is a very recent and novel interest in using soft grippers and soft robotic arms on UAVs, forming Soft Areal Manipulators (SAM). However, feedback control of soft grippers and arms in combination with UAV flight control is also a very challenging task and requires the integration of sensors into these soft-bodied systems. In general soft robotics, there is a main focus on mechanical sensing using strain sensors, where many different sensing principles such as resistance, capacitance, piezoelectricity, optical fibers, or magnetics are proposed. However, the main problems of these sensors are their wiring and integration on or in the soft structure.

An alternative are optical sensors based on vision, since they provide easier fabrication and less wiring combined with relatively high spatial precision. Vision-based tactile sensors usually use a deformable body as the sensing medium and apply a camera to capture the deformation of the medium. Marker patterns may be printed on or in the sensing medium, and the motion of the markers are tracked from the embedded camera. However, all these sensors only detect deformations of surfaces with complex computer vision but do not directly measure strain or forces. Recent research in soft matter physics on Cholesteric Liquid Crystal (CLC) Elastomer (CLCE) mechanochromism offers a revolutionary novel approach to vision-based strain sensing. CLCs spontaneously form a supramolecular helix, leading to Bragg reflection (structural colour) of circularly polarized light. When a CLC is polymerized into a CLCE, a very interesting material arises, combining the striking optical properties of a cholesteric phase with the viscoelasticity of a rubber. Because of the coupling between the cholesteric helix and the elastomeric network, a mechanical deformation changes the reflection colour, as well as the polarization. This mechanochromic response of a CLCE can enable tensile and/or pressure sensors capable of visualizing complex mechanical strain in many objects. The response is continuous and local and can be detected with cameras, hence CLCEs allow the design of novel vision-based strain and force sensors, which might also be very beneficial in soft robotics and soft aerial manipulation.

Therefore, this interdisciplinary project COSAMOS focuses on the development of a novel vision-based strain and force sensing concept using CLCEs, the design of first soft aerial grippers and robotic arms with integrated CLCE sensors and the development of a related suitable control concept for SAMs. The solutions will be integrated to experimental SAM prototypes and finally tested in two demonstrations based on realistic use cases.

Principal Investigator

Ines Chihi

Project title

Smart Monitoring System Diagnosis And Self-healing Approaches For Sustainable Manufacturing (SMOD-SHA)

Host institution

University of Luxembourg

FNR Committed

€564,000

Abstract

SMOD-SHA project aims to develop a smart system, bringing together, in a SM system, the multi-fault diagnosis, the self-healing and fault-tolerant approaches. The proposed system is challenging, especially, when integrating the multi-fault aspect of the SM system and its complex and heterogeneous structure that can be described by multi-models. SMOD-SHA project has a significant positive impact on sustainability, i.e. improves response time and enables for minimization of potential failures in the manufacturing process thus saving cost and time while maintaining operational efficiency, making accurate predictions when the machines need to be fixed and reducing energy consumption. As a result, we will have a high-quality manufacturing process optimization resource and energy consumption. In another word, robust and resilient manufacturing process.

Subcategory: Fintech/RegTech and transformative applications of distributed ledger technologies – 2 projects

Principal Investigator

Roberto Steri

Project title

Applied Contracting And Quantitative Incentive Theory (ACQUIT)

Host institution

University of Luxembourg

FNR Committed

€776,000

Abstract

The theory of financial contracting offers powerful tools to implement efficient decision making in private and public organizations. Optimal contracts provide arrangements that are compatible with the incentive constraints induced by private interests that hinder organizational efficiency. However, the applicability of the theory is still limited as quantifying the predictions of contracting and incentive models using available data poses technical and conceptual challenges.

This project takes a step towards closing the gap between theory and practice by enlarging the empirical content and applicability on the theory. The project takes advantage of modern computational and econometric tools to offer applications to four broad areas in financial economics. In corporate finance, I assess the quantitative importance of managerial beliefs and optimally-designed compensation contracts in shaping corporate policies. In auction theory, I design optimal procurement auctions for a financially-constrained buyer with implications for large-scale applications such as governmental purchases of pharmaceuticals (e.g. Covid19 vaccines). In public policy, I assess whether interventions are effective to address credit market failures and stimulate recovery during the Covid19 crisis. In financial markets, I show that the study of financial contracts between firms and external lenders provide helpful tools to track price fluctuations of financial securities.

Principal Investigator

Alex Biryukov

Project title

Advanced Cryptography For Finance And Privacy (CryptoFin)

Host institution

University of Luxembourg (SnT)

FNR Committed

€876,000

Abstract

In the past 10 years, blockchain technology (which underpins decentralized digital currencies and smart contracts) has been one of the most fertile research domains in computer science. Due to their decentralized nature and the need for a consensus mechanism, blockchains have created a number of novel and unique research challenges. The FNR CORE project FinCrypt tackled some of these challenges and came up with promising solutions to real-world problems in the context of blockchain applications and smart contracts. However, along with the rapid growth of digital currencies and the ever-increasing value of assets linked to blockchains, various new attack vectors have emerged and the limitations of current blockchain technologies regarding scalability and privacy become more and more apparent. Consequently, the need for research in the blockchain and smart contract domain is bigger than ever before. The proposed research builds on the success of the earlier FNR FinCrypt project but shifts the research focus towards scaling solutions and advanced cryptography for blockchains. The mission of the CryptoFin project is to seek innovative solutions for some of the most pressing open research problems in the blockchain domain, especially in the context of Layer-two (L2) protocols for off-chain transactions (e.g. Ethereum) and the design of advanced cryptographic techniques like Verifiable Delay Functions (VDFs), Proofs-of-Work (PoW) with special features and new MPC/SNARK-friendly primitives. Due to its timely nature and practical relevance, the proposed research has the potential to advance the state-of-the-art and create significant real-world impact.

Subcategory: Fundamental tools and data-driven modelling and simulation – 2 projects

Principal Investigator

Thomas Raleigh

Co-PI: Leon van der Torre

Project title

The Epistemology Of A.I. Systems (EAI)

Host institution

University of Luxembourg

FNR Committed

€678,000

Abstract

Artificial Intelligence is playing an increasingly important role in our lives: from recommending specific products and websites to us, to predicting how we will vote in elections to driving our vehicles. It is also being used in ethically and socially important domains like healthcare, education and criminal justice. AI has the potential to greatly increase our knowledge by helping us make new scientific discoveries, prove new theorems and spot patterns hidden in data. But it also poses a potential threat to our knowledge and reasoning by ‘nudging’ us towards some kinds of information and away from others, creating ‘internet bubbles’, by reinforcing biases that are present in ‘Big Data’, by helping to spread and target political propaganda, by creating ‘deep-fake’ images and videos as well as increasingly sophisticated and human-like texts and conversations. The fundamental aim of this project is to investigate how we can rationally respond to the outputs of artificial intelligence systems and what is required to understand and explain AI systems. This is a topic that requires an inter-disciplinary approach, drawing on both computer science to investigate the details of recent AI advances but also on philosophy to investigate the nature of rationality, understanding and explanation. The issues here are especially important since many of the most powerful recent advances in AI have been achieved by training ‘Deep Neural Networks’ on vast amounts of data using machine learning techniques. This creates the unusual situation where even the designers and creators of these AI systems admit that they do not fully understand its internal processes or how the system will process new data. It is vital then that we investigate how we might produce explanations of the behaviour of these systems that humans can actually use and understand. It is also vitally important to investigate when and how it can be rational for human consumers to trust the outputs of systems trained via machine learning despite the fact that we lack full knowledge of their internal functioning or the data that was used to train them. One of our main hopes for this project is that we will be able to develop new ways of measuring how explain-able or how trust-worthy an AI system is that could eventually be implemented by computers.

Principal Investigator

Jean-sébastien Sottet

Co-PI: Cedric Pruski

Project title

Model-driven Digital Twin Semantic Drift (MDDT-SD)

Host institution

Luxembourg Institute of Science and Technology (LIST)

FNR Committed

€669,000

Abstract

In this project, we deal with different aspects of the design of a complex system that requires a global view of a given problem. Let’s take for instance the case of mobility: usually we solve local traffic congestion (public or private) with ad-hoc solutions. However, the solution impacts on the other transports means, over transportation network, and on the passengers, is rarely taken into account before problems occurs elsewhere. The pain-point to address is then to build a holistic representation for the overall mobility, on the country and its borders; thus requiring to collect all the viewpoints from all the stakeholders and then associating them consistently. The challenge addressed here is to be able to associate all the different viewpoints into a coherent whole, where each party understand each other and the related impacts: a model federation. This model federation can be used to answer all the questions we can ask about a system, in the context of mobility: it should provide answers to the passengers, up to the policy maker (efficiency of a regulation) passing by the drivers, urban planners and network managers.

Subcategory: Social migration and social cohesion / cultural identities, cultural heritage and nationhood – 4 projects

Principal Investigator

Christophe Sohn

Project title

The Impact Of Rebordering On Cross-border Cooperation. A Social Semiotic Approach To Borders’ Symbolic Meaning (BOMIOTICS)

Host institution

Luxembourg Institute of Socio-Economic Research (LISER)

FNR Committed

€749,000

Abstract

In the wake of the COVID-19 pandemic, there has been a global increase in travel bans and several national borders have been closed outright for many weeks or even months. Following Brexit and the migration and asylum crisis of 2015–16, these border closures represent another signal of the resurgence of national borders in the political agendas of European states. In addition to the difficult practical consequences for everyday life, the rebordering dynamics call into question the future development of cross-border regions, with important social, economic and political implications.

Against this background, the overall goal of the BOMIOTICS project is to assess the extent to which the hardening of the intra-Schengen border regime is challenging the significance of supposedly open borders for cross-border cooperation (CBC) and cross-border region-building. More specifically, it will involve analyzing how rebordering affects the ways in which borders are mobilized as symbols by local CBC actors for the political construction of cross-border urban agglomerations. The premise underlying this project is that the significance of national borders does not merely diminish with CBC and regional integration. As the role of borders changes, their transformation is accompanied by a process of “symbolic recoding” intended to give them new meanings. Provided they are recoded accordingly, borders may play an important role in the formation of regional identities and the legitimization of cross-border territorial projects. Hence, to understand the extent to which rebordering is likely to modify the role and meaning of borders in CBC initiatives, it is necessary first of all to look at the way in which borders are used by local actors as means for meaning-making. Given the research issue to be addressed, theories of social semiotics that pay attention to the way actors use signs and symbols to create meaning and communicate it in specific situations will be mobilized. Four specific objectives required to meet the goal of the project are defined: (1) elaborating a conceptual framework informed by social semiotics and adapted to the case of border symbolism; (2) analyzing borders’ symbolization strategies at work based on case studies; (3) examining more specifically the material form of borders in space and the political implications of their visibility or invisibility; (4) assessing the impact of rebordering dynamics on CBC discourses and border symbolism.

The empirical analysis will focus on four cross-border urban agglomerations that constitute emblematic cases of cross-border regionalism in Europe: the Alzette-Belval European Grouping of Territorial Cooperation (EGTC) along the French-Luxembourg border, the European Twin City Frankfurt (Oder)-Słubice at the German-Polish border, the Trinational Eurodistrict Basel at the triple point between Switzerland, France and Germany, and Greater Geneva along the French-Swiss border. The investigation of the symbolization strategies at work in these “laboratories of integration” will rely on discourse analysis focusing on CBC actors’ narratives (i.e., official documents and interview transcripts) and the images (i.e., maps and photographs) they use. This approach will consider different methods of expressing ideas, concepts, or beliefs; thereby representing an innovative and substantial contribution to a better understanding of the symbolic role of borders in the shaping of regional imaginaries, the political construction of cross-border spaces, and the capacity of CBC projects to face the challenges posed by rebordering.

Principal Investigator

Christoph Purschke

Project title

Tracing Attitudes And Variation In Online Luxembourgish Text Archives (TRAVOLTA)

Host institution

University of Luxembourg

FNR Committed

€523,000

Abstract

In recent years Luxembourgish has gotten a lot of attention. Its special role in the complex multilingualism of Luxembourg has caused heated debates in the media. At the same time, people have started to use Luxembourgish as a written language only recently, largely through social and digital media. Both developments are at the center of the project TRAVOLTA. Using digital texts from RTL.lu, the project takes a close look at how Luxembourgish develops into a fully fledged standard language in real time. Additionally, it analyses central topics in the public discussion about multilingualism by investigating the opinions expressed in user comments to news articles. In doing so, the project harnesses advanced methods from machine learning to research the dynamics of public discourse and the central role of Luxembourgish in this regard.

Principal Investigator

Denisa Sologon

Project title

Spatial Economics Of Income Distribution Across Borders: Drivers Of Spatial Inequalities Using Microsimulation (SPIN)

Host institution

Luxembourg Institute of Socio-Economic Research (LISER)

FNR Committed

€792,000

Abstract

Place is important for a household’s standard of living. The pattern of economic activity influences where employment is, whilst population centres, local facilities and house prices influence where people live. There is a great deal of variation across space, as families make choices concerning where they work and where they live. When considering a household’s standard of living as the income remaining once non-discretionary expenditures have been made (e.g., housing, commuting and childcare), there are significant variations across space and within areas. This is an important issue in relation to public policy, in terms of targeting the progressive policy system and mitigating place-based inequalities. Luxembourg and the Greater Region have specific problems, as they are highly dependent on cross-border commuting as part of the dynamic labour market, and this is to a greater extent than any other area in Europe. The factors that shape inequalities in living standards are thus extremely complex involving market incomes, local housing markets, the cost of commuting and public policy. For many, the situation is doubly complicated by interacting with two separate policy environments if they work in one country and live in another.

While there is a good understanding of the factors that influence inequality at national levels, there is a poor understanding regarding the local level and even less in relation to the inequalities that exist in a cross-border region. Building on the foundations that have been developed by members of our research team over 20 years, we will develop a unique analytical infrastructure to assist in understanding the pattern of the spatial inequalities in living standards. The research programme will bring together experience in developing the Europe-wide public policy simulation tool EUROMOD, but will extend it to cover cross-border arrangements and to downscale analysis to the local level. It will utilize a novel framework developed by our team to explore the drivers of income inequality and extended during the COVID crisis to understand its impact on households’ living standards. It will also build on expertise in the team to model commuting and housing costs.

Combining our understanding of all the drivers of spatial inequality at the household level, we will unpick the relative importance of these components in shaping household income and its pattern across space in Luxembourg, as well as in the wider commuting region in neighbouring countries. We will also look at differential incentives that relate to cross-border commuting and migration decisions.

We will share our knowledge with policymakers at local, national and European levels to help in the design of better public policy. This could improve the economic dynamism of the region and mitigate some of the challenges that result from the economic changes that affect different people in different ways across space.

Principal Investigator

Francois Maniquet

Project title

Unconditional Social Assistance And Unemployment Benefits (UNSASSUB)

Host institution

Luxembourg Institute of Socio-Economic Research (LISER)

FNR Committed

€577,000

Abstract

European welfare states are in crisis. It is customary in political and academic debates to criticize them based on their inability to meet new challenges linked to inequality, globalization, or technological changes. Among the many proposals that are currently on the table to reform welfare states, one is receiving a lot of attention: lifting the current conditions that social assistance beneficiaries or unemployed workers must fulfil to be eligible to these transfers. Such a reform is often called the universal basic income proposal.

The two main conditions are:

1) be ready to take a job when one becomes available and

2) not live with a wealthy partner.

Surprisingly, economists up to now have poorly dealt with these conditions. Indeed, when studying how workers should be taxed and who should be entitled to social assistance and unemployment benefits, economists wrongly assume that workers who voluntarily quit their job are eligible to unemployment benefits and partners of wealthy workers are entitled to social assistance. We address this shortcoming in this proposal. That requires to two major changes. First, we need to redefine the social objective that the redistribution system is supposed to follow, to consider that this system may treat differently those who quit their job voluntarily from those who are fired, and those who live with a wealthy partner from those who don’t. Second, we need to re-estimate the behavioral effect of fiscal reforms. Indeed, lifting any of the two conditions to social assistance and unemployment benefits that we are interested in is likely to have behavioral effects: many workers are likely to quit their job voluntarily and request social assistance benefits if they are no longer conditional on being ready to take a job, and many voluntarily unemployed people living with wealthy partners are likely to request social assistance should it stop to be conditional to the lack of means of the partner. The expected outcomes are the identification of optimal redistribution systems in Belgium, France, Germany, Luxembourg, and the UK, and the simulation of the impact of fiscal reforms aiming at removing conditionality on the distribution of welfare in these countries. The five countries are chosen because of their large heterogeneity in the way they tax low incomes.

Subcategory: Climate change: energy efficiency and smart energy management, resilient eco- and agrosystems – 3 projects

Principal Investigator

Hui Huang*

Project title

Low-cost Real-time Soil Monitoring Solution Using Lora Radio-frequency Signals (SoilRF)

Host institution

University of Luxembourg (SnT)

FNR Committed

€539,000

Abstract

As the population continues to grow, the use of ICT technology to increase the yield and quality of agricultural products while reducing the environmental impact of agricultural activities has become an important topic. Soil sensing technology is an important building block in smart agriculture, which is of great significance for precise irrigation and optimization of soil treatment plans. It helps to solve the problems of what is needed, when is needed, and where is needed with respect to the recovery capacities of the natural resources. Different classes of soil sensors have been invented over the last few decades to estimate soil properties by measuring soils’ surrogate properties. However, the high deployment costs hinder the wide application of soil sensing technologies.

The SoilRF project aims to address the issue by exploring the sensing capability of LoRa wireless signals in real-time soil monitoring applications. It plans to conduct extensive lab experiments and field trials to understand the impacts of soil properties on the time-frequency characteristic of received underground LoRa signals and develops innovative methodologies and systems to estimate soil properties that are of interest to many smart agriculture applications. By reusing the LoRa communication network, the proposed project has the potential to provide sensorless soil sensing solutions to reduce deployment and maintenance costs significantly. The success of the SoilRF project enables innovative applications with environmental and socio-economic impacts for IoT-based smart agriculture applications. Together, the project contributes to the cost-effective solution to those problems that farmers are facing: shortages of water, cost management, and productivity issues.

Principal Investigator

Martin Stierle

Project title

Building A Green Patent Framework To Foster Sustainable Development (BUGPAF)

Host institution

University of Luxembourg

FNR Committed

€478,000

Abstract

Climate change is one of the major challenges of the 21st century. Societal, economic and environmental sustainability has become the key answer to mitigate its effects but mankind must react quickly to stand a chance to limit further damages. Technology and innovation lay a crucial foundation to face and successfully overcome the challenge.

The patent system is considered to be a key instrument to induce investments in research and development (R&D). Its rationale lies in the encouragement of private parties to create innovation by the prospect of exclusive use. The legal framework as it stands, however, does not distinguish between sustainable and non-sustainable technologies. The current laws do not build a specific and more beneficial framework for sustainable R&D processes in comparison to non-sustainable endeavours. The system continues to induce investments in so-called brown technologies to the same extent as it does with investments in green innovation. De facto, countless non-sustainable technologies used in the past and today have been induced by the patent framework.

The dysfunctional effects on sustainable development have been addressed by researchers since the 1970s. Patent offices have tried to overcome the situation with different Green Tech programs. Both, the academic discussions as well as the institutional efforts have shown no significant effect. In most recent years, patent applications related to green inventions have even declined at the European Patent Office. The present system does not cater for the needs of society to spur sustainable development, although the patent framework is supposed to drive technological progress and procure the relevant innovation to the benefit of society.
The proposed project will recalibrate the patent system. It will explore its potential to contribute to sustainable development and thereby align its framework with sustainability goals. It will focus on four areas: Firstly, it will investigate whether the EPO can support the attraction of funding for the development and commercialization of green technologies. Secondly, it will investigate the potential of right holders to privately enforce sustainability goals with patents. Thirdly, it will research on a potential sustainability defence to immunise cutting-edge green innovation against patent hold-ups. Fourthly, it will explore potential policy levers to make patent owners share their rights and knowledge on green technologies with competitors to foster the general deployment of sustainable inventions.

The proposed investigation will impact the discussion on intellectual property and sustainability on a national, European and international level. It will serve patent offices and legislators in their future decision-making towards a more conducive ecosystem for sustainably innovation and help to align patent policy and sustainability goals.

Principal Investigator

Jun Cao

Project title

Learning Enabled Autonomous Real-time Operation For Distribution Grids (LEAP)

Host institution

Luxembourg Institute of Science and Technology (LIST)

FNR Committed

€687,000

Abstract

The EU 2050 climate-neutrality target drives an unprecedented energy transition in Europe that will affect the future landscape of the energy sector, with more and more various distributed energy resources (DERs), such as renewable energy sources (RESs), energy storage, electric vehicles and elastic demands, connected into distribution systems.

As a result, the taxonomy of distribution grid is rapidly changing at a global scale. It is envisioned that future distribution grids will become highly granular with control and operation procedures that will be profoundly different than those of today. It is envisioned that the time windows to solve operational problems will be narrowed in future distribution grids. In order to maintain the safety and stability of DERs-driven increasingly variable operation of power systems, operational planning decisions of agents will no longer be sufficient merely on the basis of a day or a few hours in advance: most decisions must be made in situ and moving to real-time (RT) according to the instantaneous operating conditions of the distributed grids. Operational planning will evolve towards optimal control of complex systems in RT, which cannot be addressed by existing approaches.

In order to address these questions, LEAP proposes ground-breaking solutions based on computational intelligence techniques, specifically based on cutting-edge technologies such as artificial intelligence (AI) and machine learning (ML), which are emerging as major enablers to lead the energy transition. Such an intelligent digital framework will be integrated into a wider digital initiative, i.e., into a Nationwide Digital Twin (NWDT) project.

The LEAP project will reveal new knowledge and methods in the emerging energy digitalization and Artificial Intelligence for a long-term research and can support accommodating increasing renewable energy and accelerating the energy transition.”

Subcategory: Economic green sustainable finance / circular and shared economy – 2 projects

Principal Investigator

Xavier Goux*

Project title

Toward An Efficient Mesophilic Biological Methanation (eBioMeth)

Host institution

Luxembourg Institute of Science and Technology (LIST)

FNR Committed

€589,000

Abstract

Biological methanation (BM) allows for the conversion of carbon dioxide (CO2) and dihydrogen (H2) into biomethane thanks to the activity of specific microbes. This process can be considered as fundamental to deal with the current climate challenge to reduce CO2 emissions and fossil energy use. While the world energy consumption is predicted to rise by nearly 50% between 2018 and 2050 according to the US Energy Administration (EIA), replacement of natural gas by sustainably produced biomethane is therefore a valuable fossil fuel alternative solution. With a methane content above 95%vol, biomethane obtained from biomass and/or the valorisation of CO2 from industry is suitable as an energy carrier or transportation fuel. Biomethane has the advantage of being able to benefit from the same infrastructure that is currently used by natural gas; therefore, this is also a rapid solution.

BM happens during the last step of anaerobic digestion (biogas production from biomass, such as farmyard waste), yet little is still known about the microbes involved in this specific step. Indeed, to the best of our knowledge, information about which microbes are involved in this process, which functions do they performe exactly and what controls their abundance rates, activities, and interactions are missing. It has been observed that during BM, competition for substrates such as CO2 and H2 is high. For example, hydrogenotrophic Archaea producing CH4 compete with homoacetogenic bacteria producing acetate, leading to CH4 yield loss. A knowledge gap is also existing concerning the behaviour of the BM microbiome toward process operating conditions that can be used. Thus, difficulties are observed at the experimental scale to run an efficient (e.g., mesophilic) BM in terms of CO2 conversion rate, whereby there is a high biomethane concentration rate in the final produced gas with an acceptable flow, allowing potential large industrial application.

The main objective of this research project is to study the microbial community involved in the mesophilic BM, to generate new important knowledge towards future microbial engineering.
To do so, eBioMeth will investigate the effect of different mesophilic BM operating conditions such as inoculum, hydraulic retention time, gas retention time and pH on the microbiome involved in the mesophilic conversion of CO2 and H2 and the resulting process performances. Microbial community structure, function and interactions will be characterised by 16S rRNA amplicon sequencing and metatranscriptomics. This work will be done with the view of identifying the key microbial actors and functions that provide optimal CO2 and H2 conversion into CH4. With this insight, mesophilic BM operating conditions may be adapted in a near future to naturally engineer the microbial community toward the best adapted organisms for an efficient process and push BM as a core microbial technology for the CO2 valorisation and for renewable energy production.

Principal Investigator

Thomas Schaubroeck*

Project title

Advancing And Conducting The Impact Assessment Of Circular Economy Initiatives On All Three Sustainability Pillars Through Integrated Life Cycle Sustainability Assessment, With A Focus On Pvc In The Construction Sector (CIRCUSTAIN)

Host institution

Luxembourg Institute of Science and Technology (LIST)

FNR Committed

€481,000

Abstract

The Luxembourgish and European governments ambition the implementation of circular economy to increase sustainability. Circular economy entails recycling, reuse and other similar practices, which is different from the business as usual of disposing of products through incineration etc. Although circular economy sounds promising, we still need to analyse its sustainability and steer practices where needed. Moreover, besides probable beneficial environmental (e.g. less greenhouse gas emissions because incineration is avoided) and economic (e.g. more local profit) effects, the social implications of circular economy should as well be regarded. Studies have shown that circular economy will induce more job creation and a shift to different types of jobs.

In this project, we aim to conduct and improve sustainability assessment of circular economy initiatives considering all these aspects, with a focus on cases regarding circular economy practices for PVC in the construction sector. Hereto, we will set up a more advanced scientific framework where also two integrated effects would be considered: (1) the effect of reduced environmental impact on the health state of labour force, influencing labour availability and costs; (2) rebound effects on the environment due to more expenditure associated with job creation. To support this interdisciplinary research of CIRCUSTAIN, there will be involvement of researchers with different backgrounds and experts/stakeholders from the Luxembourgish government and industry. The outcomes will provide new insights in the sustainability impact of circular economy (distinguishing also local from global impacts), serve as template for further research, and allow to pinpoint certain measures that can be taken to improve sustainability of circular economy initiatives (e.g. delimit transportation distances for waste collection).

Subcategory: Precision medicine, including environmental, lifestyle and socio-economic factors – 5 projects

Principal Investigator

Carole Devaux

Project title

Pre-clinical Validation Of Comix And Bikes/Trikes Against Infection Of Pseudomonas Aeruginosa (PSEUDO)

Host institution

Luxembourg Institute of Health (LIH)

FNR Committed

€669,000

Abstract

Pseudomonas aeruginosa (P aeruginosa) is a bacterial member of the pulmonary microbiota that plays a crucial role in lung invasive infections such as pneumonia. Infections due to P aeruginosa has become a major health problem, especially hospital-acquired infections, in critically ill individuals, because of its resistance that render innefective most of antibiotics. Antibiotic resistance has become a major public health threat as projections on the epidemic estimated the bacterial infections mortality to be around 10 million/year in 2050. Because of resistance emergence and occurrence risk of drug-related side effects, the conventional anti-infectious therapies against P. aeruginosa appear currently limited. The opportunistic bacteria is therefore classified as priority one pathogen by the World Health Organization.

Antibodies (Abs) are promising therapeutics that can target selectively a pathogen and induce a fast immune response to clear it, but few antimicrobial Abs are currently in clinical trials. The development of Abs for treating respiratory diseases urges specific innovation for resistant bacterial strains. Innate immunity is the first line of natural defence against the multidrug resistant bacteria which can be exploited to activate the complement proteins or the Natural Killer (NK) cells that both lyse and further kill bacteria. Furthermore, bi-specific or multi-specific Abs constitute a growing class of therapeutics utilizing several different antibodies engaging the immune response against a targeted pathogen. We have produced several innovative antibody-like constructions, called as Complement-activating Multimeric immunotherapeutic compleXes (CoMiX), activating the complement proteins at the surface of the bacteria, and showing the ability to kill and reduce bacterial growth, as well as bi-specific (BiKE) and tri-specific (TriKE) Abs engaging NK cells to kill P aeruginosa.

During this project, we want to obtain, for the first time, some preclinical validation of the therapeutic efficacy of CoMiX activating the complement or the BiKes/TriKes activating NK cells in the context of a directed anti-infectious strategy that could be further implemented in patients suffering from lung invasive diseases. Our goal is to decipher more deeply the mechanisms of action of such Abs- like therapeutics against P. aeruginosa infection, by focusing on the deposition of complement proteins or the functional potency of the NK cells to eliminate the bacteria. The use of animal models will allow the proof-of-concept for their efficacy in vivo.

By reducing the impact of respiratory infections, we aim at improving the health and life comfort of patients suffering from lung invasive diseases. If successful, the results achieved in the project would encourage us to move forward to first clinical trial phases in humans.

Principal Investigator

Annika Petra Christine Lutz

Co-PI: Jean Botev

Project title

Virtual Reality Body Image Intervention And Assessment Suite (VR BIAS)

Host institution

University of Luxembourg

FNR Committed

€583,000

Abstract

VR BIAS presents a novel virtual-reality-based approach to improve body image, that is, the way someone perceives, feels, and thinks about their body. People with a negative and distorted body image are more likely to develop an eating disorder and less likely to recover from it. Distorted feelings of events happening inside the body, such as the beating of the heart, are also common in eating disorders.

Participants in our intervention view a virtual representation of their body pulsating with their heart rhythm, which creates an illusion of ownership over the virtual body. Since this intervention combines information on how the body looks with how the body feels from the inside, we expect this to positively affect the way participants experience their bodies. VR BIAS explores different variations of this illusion (various types of avatar bodies, viewing perspectives, and limb motion) and distinct ways to assess distorted perceptions of the body. Experiments measure how strongly participants experience avatar embodiment, how this improves their body image, and how they generally feel during the experience. We combine self-report and behavioural assessments with state-of-the-art psychophysiology (e.g., brain waves, skin temperature).

VR BIAS will hence provide assessment tools for research and clinical practice, an intervention technique for the treatment of eating disorders (potentially also body dysmorphic disorder and overweight/obesity), and contribute to current psychological and neurobiological theories of body image disturbance and eating disorders. Drawing on interdisciplinarity and innovative technology, VR BIAS potentially has a direct health impact on people suffering from or at risk for eating and weight disorders.

Principal Investigator

Sebastian Scheer

Project funded together with Fondation Cancer

Project title

Epigenetic Control Of Nk Cell Function (EPICON)

Host institution

Luxembourg Institute of Health (LIH)

FNR Committed

€963,000

Abstract

The reasons to develop cancer are highly diverse. For instance, changes in the DNA of skin cells caused by too much UV light may lead to changes in this cell, which can make them proliferate more than usual. Ultimately, this is one way of how a regular cell can become a cancer cell and in fact, this is what happens every second in each of our bodies and is not restricted to skin cells. However, we have developed a very efficient system during evolution that is very good at detecting these cancerous cells and is very efficient at eliminating them: the immune system. Albeit its high efficacy, the immune system is not perfect in detecting all cancerous cells and undetected cancerous cells are therefore able to escape the immune surveillance mechanisms and start growing to a solid tumour or spread throughout the bloodstream as so-called blood cancers. In recent years, many researchers focussed on the highly important question as to why the immune system is unable to identify and eliminate cancerous cells in patients. It is especially important to identify ways to improve individual cells of the immune system to detect cancerous cells or to improve their efficacy. However, we still do not know enough about even basic mechanisms that drive the efficacy of immune cells. Consequently, EPICON is dedicated to identifying basic principles that can improve the efficacy of one of the most effective killers of cancerous cells in the bloodstream: the natural killer (NK) cell.

The DNA, representing the blueprint for proteins and other molecules, is the same in each cell of the body. However, we can appreciate that a skin cell is very different to a cell in your eyes. The reason for this discrepancy is the fact that epigenetic mechanisms are different for each cell. Epigenetics is a summary term that governs the changes in proteins and even modification to the DNA itself, however, does not include changes in the DNA sequence itself. The epigenetic status of a cell therefore defines which proteins can be made from the DNA and since this is different in each cell, the epigenetic status ultimately defines the identity of the cell.

EPICON builds on strong preliminary data that 1) shows that the epigenetic modifiers can maintain NK cell integrity and transcription factor usage, which is a possible mechanism to improve the treatment of patients with cancer, and 2) inhibition of specific epigenetic modifiers can lead to improved NK cell function.

Despite the compelling evidence that epigenetic modifiers can be targeted to improve effector cell function, the tools to identify individual epigenetic modifiers are limited. As such, there is not a complete set of small molecule inhibitors that could be used to identify individual roles in NK cell function. EPICON will therefore make use of an in vivo CRISPR screen, where individual epigenetic modifiers will be deleted in NK cells and their function subsequently tested in preclinical models of cancer. In addition, we will perform in vivo and ex vivo studies to identify the mechanisms underlying the effect of individual epigenetic modifiers.

Overall, EPICON is designed to lay the groundwork for improving adoptive NK cell-based therapies in patients with cancer.

Principal Investigator

Torsten Bohn

Project title

Interactions Of Carotenoids And Dietary Fiber – Implications For Bioavailability And Colonic Degradation (CaroFiber)

Host institution

Luxembourg Institute of Health (LIH)

FNR Committed

€793,000

Abstract

Background: Carotenoids are colourful pigment, present in many plants, fungi and bacteria. Humans cannot synthesize them. Interest in carotenoids has been mounting as their dietary intake, as well as their levels in the bloodstream have been related to reduced incidence of various chronic diseases, such as type 2 diabetes, but also total mortality. In addition, some of these liposoluble microconstituents can be converted by the human body into vitamin A, important for growth and the immune system. Last but not least, low intake of certain carotenoids, i.e. lutein and zeaxanthin, is associated with age-related macular degeneration, the most common cause of vision loss in the elderly.

Carotenoids and fiber: Though carotenoids can be found in many plant foods, their bioavailability (i.e. the fraction of a nutrient that the body is able to absorb and utilize) is low and quite variable – depending on the food matrix, and also on personal factors of the host, such as genetic background. While it is know that dietary lipids and possibly certain proteins can positively influence the bioavailability of carotenoids, it appears that certain dietary fibers can hamper them, while others, especially prebiotics, may have no effect, or may hypothetically even enhance bioavailability. However, dietary fibers occur in many various forms in nature, with many different functionality, and their effect on carotenoids during digestion has not truly been studied systematically. For instance, some fibers such as inulin are rather soluble, and of small molecular size, less likely to negatively interfere with carotenoid absorption. They can be also be metabolized by the bacteria in the intestine, which may have additional health benefits. Other fibers, such as cellulose are almost insoluble but owing to their macromolecular structure more likely to interfere with carotenoid bioavailability. They can hardly be fermented by the bacteria in the gut. However, the intake of dietary fiber is generally desired and should not be reduced, as already fiber intake in especially developed countries is marginal.

Project aims and methods: Therefore, the present project aims to study the impact that different types of dietary fiber could have on carotenoids during gastro-intestinal digestion. Their effect on different types of carotenoids will be studied, both individually, and from food matrices, by using an accepted digestion model. As carotenoids, with or without dietary fiber, could also potentially influence gut microbiota, such aspects will also be studied. In additional, carotenoid breakdown products and metabolites, which may be bioactive and available for absorption in the colon, will also be investigated. A final human study with 24 volunteers will strive to confirm findings generated in vitro in the laboratory. In this study, each person will consume three different test meals with different types of dietary fiber (2 meals) and one control meal, separated by a one week period.

Relevance: This project is expected to reveal which dietary fiber may be especially hampering carotenoid availability, and which type has no influence or may even improve it. In addition, it will reveal new insights into the colonic fate of carotenoids. The results will be relevant especially for persons with low preformed vitamin A intake (vegetarians, people living in countries with low meat intake), and also for the general population in sight of the health relevance of these pigments.

Principal Investigator

Pascale Engel De Abreu

Co-PI: Robert Kumsta

Project title

The Effects Of Childhood Adversity On Mental Health And Learning: A Nationwide Longitudinal Project With Children In Alternative Care In Luxembourg (CHAMP)

Host institution

University of Luxembourg

FNR Committed

€999,000

Abstract

Children raised in alternative care have been separated from their parents and placed to live in an institutional home or in family-based foster care. Many of these children have experienced severe adversity and trauma in their homes, such as physical abuse or emotional maltreatment, which led to the separation from their family of origin. The aim of alternative care is to protect children from harm and to offer a safe and caring environment that fosters development and growth. Nevertheless, children raised in alternative care are a high-risk group for poor developmental outcomes. Far too many present mental health problems, learning and language difficulties, and poor educational results. Although children in alternative care are at higher risks of mental health and learning problems than children not in care, there is a dearth of data on these children’s development and consequently their mental health and educational needs remain poorly understood.

This study aims to determine how many children in the Luxembourg alternative care system present mental health problems and learning difficulties. Towards this end, the study will follow over 700 children and adolescents aged between 4 and 16 years growing up in different forms of alternative care. Over three years, adolescents between 11-16 years will complete questionnaires once a year on their mental health and learning. Children between 4 and 10 years will be directly assessed twice during these three years with tasks that the children complete together with a researcher. The study establishes basic prevalence rates of mental health and learning problems. The project also aims to discover which specific external and internal protective and risk factors are related to mental health and learning in children and adolescents in alternative care. The study will explore specific mechanisms by which early adversity and trauma may affect mental health and learning. Children will provide a DNA sample for epigenetic testing and they will complete tests of executive function. Epigenetic modification, related to mechanism of how genes are “switched on and off”, and executive functions have both been suggested to influence mental health and learning. Caretakers will also be asked about children’s placement and maltreatment histories. All this information will be used to create statistical models that test whether and how various contextual, biological and psychological factors relate to children’s mental health and their learning.

This is the first study in Luxembourg to collect these important data. It will generate essential findings that can inform policy and practice in Luxembourg. The study is also internationally relevant as it is among the first to explore relationships with a broad range of risk and protective factors including contextual and psychological factors as well as epigenetic alterations. This will lead to a more comprehensive understanding of how early adversity affects mental health and learning at the biological and the psychological level. This information can be used in the future to develop more effective interventions and support services for children in alternative care.

Subcategory: Understanding, preventing, and treating the health-disease transition – 3 projects

Principal Investigator

Bjorn Becker*

Project funded together with Fondation Cancer

Project title

Targeting Aldh1l2 To Enforce Er Stress Sensitivity Of Cancer Cells (1cRedOx)

Host institution

Luxembourg Institute of Health (LIH)

FNR Committed

€498,000

Abstract

Our project’s aim is to test a new and unexplored treatment approach for preventing colorectal cancer (CRC) progression. CRC is one of the most frequent cancer types worldwide and leads to an estimated amount of 1 million deaths per year. The lack of efficient therapies as well as the poor prognosis for metastatic CRC has motivated us to find a more specific therapeutic target point to suppresses CRC proliferation.

Within our preliminary data, we identified a potential target in form of a promising metabolic compensatory mechanism that is important to balance cellular stress. More precisely, we showed that an enzyme (namely ALDH1L2) of the folate metabolism gains activity upon certain cellular stress conditions to guarantee cancer cell survival. 1cRedOx aims to exploit this novel knowledge by combining an inhibition of ALDH1L2 with local induction of a specific stress stimulus. Thereby, we intend to disturb the cancer cell`s ability to survive the applied stress stimulus, which would consequently reduce CRC growth and metastasis. In a proof of principle experiment, we have already demonstrated that this combinatory intervention strategy is indeed suited to diminish cancer cell growth in vitro.

Since the general contribution of ALDH1L2 activity to CRC progression is poorly understood until now, we will use state-of-the-art cell culture approaches to further define the underlying molecular mechanism(s) that are responsible for the observed growth reduction upon combinatorial therapy. Moreover, we will evaluate the therapeutic potential of this innovative treatment on primary tumour growth and metastasis formation in preclinical CRC models. As a long-term perspective, our project will build a basis for translation of our treatment approach into the clinic and might thereby help to improve the therapy of CRC patients.

Principal Investigator

Leslie Ogorzaly

Project title

Aptasensors As An Emerging And Convenient Tool To Improve The Multiplex Detection Of Foodborne Viral Diseases (APTAVIR)

Host institution

Luxembourg Institute of Science and Technology (LIST)

FNR Committed

€683,000

Abstract

As devastating as it has been, the current COVID-19 pandemic has raised awareness among policymakers and the global population of the potential scourge of viral diseases. Yet other epidemics or pandemics have already marked the last 20 years, such as those caused by SARS-CoV-1, MERS-CoV, several strains of influenza, HIV, Ebola, Zika. There are hundreds of infectious viral diseases that can be transmitted through person-to-person contact, air, water or food. Of these, food- and water-borne viral diseases are too often underestimated as a global concern because their actual burden is difficult to quantify. Viruses are able to change rapidly and thus adapt to new contexts. This has been the case for hundreds of years and will continue to be the case despite our increasing knowledge of these microorganisms and how they work. It is essential to learn from our past experiences and to exploit new solutions arising from innovation to minimise the occurrence and spread of such dramatic events in the future. In particular, it is certain is that humanity now needs the most efficient and cost-effective tools to detect this global scourge widely and as early as possible. An interesting and promising approach to the development of such detection tools is the use of aptamers. Aptamers are a small, single-stranded nucleic acid (DNA or RNA) capable of adopting a three-dimensional structure that gives it remarkable specificity and affinity for its target. The in vitro selection process is also a major advantage, allowing aptamers to be customised indefinitely to achieve the desired features. Aptamer technology began to be developed in the early 1990s and has been very successful over the last decade, particularly in virology. However, despite this, the number of aptamers used outside of research activities is very limited, probably due to the lack of awareness of this technology and the supremacy of antibodies and genome amplification tools for many years in microbial diagnostics. However, aptamers are molecules with extraordinary potential.

Therefore, the APTAVIR project propose to develop an innovative diagnostic tool based on DNA aptamers to monitor the main foodborne viruses in environmental, water, food or clinical samples. The long-term objective is to bring to market a new generation of diagnostic kits, which will allow efficient, sensitive, rapid and inexpensive detection of viruses of interest. To this end, APTAVIR will design new aptamers for major families of foodborne virus and implement them in two detection platforms. The first one is a lateral flow test, such as the COVID-19 self-tests, that can be used widely for covering the massive testing needs for the control of an epidemic situation, while the second one will be a fluorescent biosensor, more dedicated to laboratory testing to assess risks of contamination exist throughout the food chain “farm to fork”, including water. The results emerging from this state-of-the-art project and the associated future technological developments will contribute to reducing the burden of foodborne diseases and improving public health by paving the way for a strategic cost-effective diagnostics solution for the surveillance of foodborne viral disease and possibly beyond.

Principal Investigator

Carole Linster

Project title

Whole Organism Models To Dissect The Pathophysiology Of A Recently Identified Rare Pediatric Neurometabolic Disorder (NAXDivo)

Host institution

University of Luxembourg

FNR Committed

€999,000

Abstract

Our cells contain thousands of different chemicals (called metabolites) which are formed and transformed by specific proteins called enzymes. Of these metabolites, some are prone to damage and therefore need to be protected or repaired. Our cells have developed sophisticated mechanisms for protection and failure of those can lead to accumulation of damaged metabolites. NADH and NADPH are such vulnerable metabolites (crucial for the functioning of enzymes), having the tendency to get damaged. Our laboratory discovered a pair of enzymes (called NAXD and NAXE) that rectify this damage. Very recently, we also realized that children with a genetic defect in the NAXD or NAXE enzymes develop a brain disorder, and invariably die prematurely due to severe illness. These children are born normally, show normal development and learning behavior, but when faced with a normally benign fever or infection, start showing symptoms including severe skin rashes and neurological impairments. A dietary supplement (niacin, also called vitamin B3) has shown some promise for the treatment of this severe disorder. However, we do not understand in sufficient detail how the disease starts, progresses, and leads to neuronal death in affected children, nor do we understand how vitamin B3 protects these children. The beneficial results obtained for a few patients with the vitamin B3 treatment, and a better understanding of the disease mechanism could serve as a promising starting point to develop more efficient and specific therapeutic approaches.

Here we propose to develop a mouse model of NAXD deficiency as it comes closer to the human system and may generate more disease relevant insights than the cellular disease models that we have studied so far. We will also work with zebrafish models of NAXD deficiency that we already generated, and which will allow to address some of our research questions in a more time- and cost-efficient way and/or using complementary methods. Research with these models will allow us to analyse how a rare disease such as NAXD deficiency develops within the complexity of a whole organism. We also plan to use the models to test how vitamin B3 exerts its therapeutic effects and if better alternatives can be proposed. This project should set an example of how such disorders, even if less common, should be studied.

Successful completion of the project would further our understanding of how NAXD deficiency leads to severe disease in children, providing a strong basis for devising treatment strategies and starting to test them in the generated disease models. This research ultimately aims to improve the situation of affected children and their families and the insights gained may also help to progress in our understanding of more common neurodegenerative diseases.

Subcategory: Complex biomedical systems – data and models – 1 project

Principal Investigator

Jens Schwamborn

Project title

Midbrain-striatum-assembloids To Model Synapse Function Alteration In Parkinson`S Disease (MidStriPD)

Host institution

University of Luxembourg

FNR Committed

€769,000

Abstract

A specific type of neurons secretes the neurotransmitter Dopamine. These neurons are localized in a region of the brain called the midbrain. From there they send long projects to another region, called the striatum. In the striatum Dopamine is released, which is important for muscle movement. During Parkinson`s disease these dopaminergic neurons die. Current cell culture models for Parkinson`s disease are not able to fully recapitulate the setting of midbrain and striatum in the cell culture dish. Therefore, we here propose to use Parkinson`s disease patient specific stem cells to generate 3D cell culture representatives of midbrain and striatum and to connect them to build a structure that is similar to the brain situation. In this structure we want to study if connectivity between the regions is changed in the disease and whether we can restore a correct connectivity in order to rescue the loss of dopaminergic neurons. We hope that this approach will bring us one step closer to a treatment for Parkinson`s disease.

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