Project acronym A-DATADRIVE-B
Project Advanced Data-Driven Black-box modelling
Researcher (PI) Johan Adelia K Suykens
Host Institution (HI) KATHOLIEKE UNIVERSITEIT LEUVEN
Call Details Advanced Grant (AdG), PE7, ERC-2011-ADG_20110209
Summary Making accurate predictions is a crucial factor in many systems (such as in modelling energy consumption, power load forecasting, traffic networks, process industry, environmental modelling, biomedicine, brain-machine interfaces) for cost savings, efficiency, health, safety and organizational purposes. In this proposal we aim at realizing a new generation of more advanced black-box modelling techniques for estimating predictive models from measured data. We will study different optimization modelling frameworks in order to obtain improved black-box modelling approaches. This will be done by specifying models through constrained optimization problems by studying different candidate core models (parametric models, support vector machines and kernel methods) together with additional sets of constraints and regularization mechanisms. Different candidate mathematical frameworks will be considered with models that possess primal and (Lagrange) dual model representations, functional analysis in reproducing kernel Hilbert spaces, operator splitting and optimization in Banach spaces. Several aspects that are relevant to black-box models will be studied including incorporation of prior knowledge, structured dynamical systems, tensorial data representations, interpretability and sparsity, and general purpose optimization algorithms. The methods should be suitable for handling larger data sets and high dimensional input spaces. The final goal is also to realize a next generation software tool (including symbolic generation of models and handling different supervised and unsupervised learning tasks, static and dynamic systems) that can be generically applied to data from different application areas. The proposal A-DATADRIVE-B aims at getting end-users connected to the more advanced methods through a user-friendly data-driven black-box modelling tool. The methods and tool will be tested in connection to several real-life applications.
Summary
Making accurate predictions is a crucial factor in many systems (such as in modelling energy consumption, power load forecasting, traffic networks, process industry, environmental modelling, biomedicine, brain-machine interfaces) for cost savings, efficiency, health, safety and organizational purposes. In this proposal we aim at realizing a new generation of more advanced black-box modelling techniques for estimating predictive models from measured data. We will study different optimization modelling frameworks in order to obtain improved black-box modelling approaches. This will be done by specifying models through constrained optimization problems by studying different candidate core models (parametric models, support vector machines and kernel methods) together with additional sets of constraints and regularization mechanisms. Different candidate mathematical frameworks will be considered with models that possess primal and (Lagrange) dual model representations, functional analysis in reproducing kernel Hilbert spaces, operator splitting and optimization in Banach spaces. Several aspects that are relevant to black-box models will be studied including incorporation of prior knowledge, structured dynamical systems, tensorial data representations, interpretability and sparsity, and general purpose optimization algorithms. The methods should be suitable for handling larger data sets and high dimensional input spaces. The final goal is also to realize a next generation software tool (including symbolic generation of models and handling different supervised and unsupervised learning tasks, static and dynamic systems) that can be generically applied to data from different application areas. The proposal A-DATADRIVE-B aims at getting end-users connected to the more advanced methods through a user-friendly data-driven black-box modelling tool. The methods and tool will be tested in connection to several real-life applications.
Max ERC Funding
2 485 800 €
Duration
Start date: 2012-04-01, End date: 2017-03-31
Project acronym ACCOPT
Project ACelerated COnvex OPTimization
Researcher (PI) Yurii NESTEROV
Host Institution (HI) UNIVERSITE CATHOLIQUE DE LOUVAIN
Call Details Advanced Grant (AdG), PE1, ERC-2017-ADG
Summary The amazing rate of progress in the computer technologies and telecommunications presents many new challenges for Optimization Theory. New problems are usually very big in size, very special in structure and possibly have a distributed data support. This makes them unsolvable by the standard optimization methods. In these situations, old theoretical models, based on the hidden Black-Box information, cannot work. New theoretical and algorithmic solutions are urgently needed. In this project we will concentrate on development of fast optimization methods for problems of big and very big size. All the new methods will be endowed with provable efficiency guarantees for large classes of optimization problems, arising in practical applications. Our main tool is the acceleration technique developed for the standard Black-Box methods as applied to smooth convex functions. However, we will have to adapt it to deal with different situations.
The first line of development will be based on the smoothing technique as applied to a non-smooth functions. We propose to substantially extend this approach to generate approximate solutions in relative scale. The second line of research will be related to applying acceleration techniques to the second-order methods minimizing functions with sparse Hessians. Finally, we aim to develop fast gradient methods for huge-scale problems. The size of these problems is so big that even the usual vector operations are extremely expensive. Thus, we propose to develop new methods with sublinear iteration costs. In our approach, the main source for achieving improvements will be the proper use of problem structure.
Our overall aim is to be able to solve in a routine way many important problems, which currently look unsolvable. Moreover, the theoretical development of Convex Optimization will reach the state, when there is no gap between theory and practice: the theoretically most efficient methods will definitely outperform any homebred heuristics.
Summary
The amazing rate of progress in the computer technologies and telecommunications presents many new challenges for Optimization Theory. New problems are usually very big in size, very special in structure and possibly have a distributed data support. This makes them unsolvable by the standard optimization methods. In these situations, old theoretical models, based on the hidden Black-Box information, cannot work. New theoretical and algorithmic solutions are urgently needed. In this project we will concentrate on development of fast optimization methods for problems of big and very big size. All the new methods will be endowed with provable efficiency guarantees for large classes of optimization problems, arising in practical applications. Our main tool is the acceleration technique developed for the standard Black-Box methods as applied to smooth convex functions. However, we will have to adapt it to deal with different situations.
The first line of development will be based on the smoothing technique as applied to a non-smooth functions. We propose to substantially extend this approach to generate approximate solutions in relative scale. The second line of research will be related to applying acceleration techniques to the second-order methods minimizing functions with sparse Hessians. Finally, we aim to develop fast gradient methods for huge-scale problems. The size of these problems is so big that even the usual vector operations are extremely expensive. Thus, we propose to develop new methods with sublinear iteration costs. In our approach, the main source for achieving improvements will be the proper use of problem structure.
Our overall aim is to be able to solve in a routine way many important problems, which currently look unsolvable. Moreover, the theoretical development of Convex Optimization will reach the state, when there is no gap between theory and practice: the theoretically most efficient methods will definitely outperform any homebred heuristics.
Max ERC Funding
2 090 038 €
Duration
Start date: 2018-09-01, End date: 2023-08-31
Project acronym ActiveWindFarms
Project Active Wind Farms: Optimization and Control of Atmospheric Energy Extraction in Gigawatt Wind Farms
Researcher (PI) Johan Meyers
Host Institution (HI) KATHOLIEKE UNIVERSITEIT LEUVEN
Call Details Starting Grant (StG), PE8, ERC-2012-StG_20111012
Summary With the recognition that wind energy will become an important contributor to the world’s energy portfolio, several wind farms with a capacity of over 1 gigawatt are in planning phase. In the past, engineering of wind farms focused on a bottom-up approach, in which atmospheric wind availability was considered to be fixed by climate and weather. However, farms of gigawatt size slow down the Atmospheric Boundary Layer (ABL) as a whole, reducing the availability of wind at turbine hub height. In Denmark’s large off-shore farms, this leads to underperformance of turbines which can reach levels of 40%–50% compared to the same turbine in a lone-standing case. For large wind farms, the vertical structure and turbulence physics of the flow in the ABL become crucial ingredients in their design and operation. This introduces a new set of scientific challenges related to the design and control of large wind farms. The major ambition of the present research proposal is to employ optimal control techniques to control the interaction between large wind farms and the ABL, and optimize overall farm-power extraction. Individual turbines are used as flow actuators by dynamically pitching their blades using time scales ranging between 10 to 500 seconds. The application of such control efforts on the atmospheric boundary layer has never been attempted before, and introduces flow control on a physical scale which is currently unprecedented. The PI possesses a unique combination of expertise and tools enabling these developments: efficient parallel large-eddy simulations of wind farms, multi-scale turbine modeling, and gradient-based optimization in large optimization-parameter spaces using adjoint formulations. To ensure a maximum impact on the wind-engineering field, the project aims at optimal control, experimental wind-tunnel validation, and at including multi-disciplinary aspects, related to structural mechanics, power quality, and controller design.
Summary
With the recognition that wind energy will become an important contributor to the world’s energy portfolio, several wind farms with a capacity of over 1 gigawatt are in planning phase. In the past, engineering of wind farms focused on a bottom-up approach, in which atmospheric wind availability was considered to be fixed by climate and weather. However, farms of gigawatt size slow down the Atmospheric Boundary Layer (ABL) as a whole, reducing the availability of wind at turbine hub height. In Denmark’s large off-shore farms, this leads to underperformance of turbines which can reach levels of 40%–50% compared to the same turbine in a lone-standing case. For large wind farms, the vertical structure and turbulence physics of the flow in the ABL become crucial ingredients in their design and operation. This introduces a new set of scientific challenges related to the design and control of large wind farms. The major ambition of the present research proposal is to employ optimal control techniques to control the interaction between large wind farms and the ABL, and optimize overall farm-power extraction. Individual turbines are used as flow actuators by dynamically pitching their blades using time scales ranging between 10 to 500 seconds. The application of such control efforts on the atmospheric boundary layer has never been attempted before, and introduces flow control on a physical scale which is currently unprecedented. The PI possesses a unique combination of expertise and tools enabling these developments: efficient parallel large-eddy simulations of wind farms, multi-scale turbine modeling, and gradient-based optimization in large optimization-parameter spaces using adjoint formulations. To ensure a maximum impact on the wind-engineering field, the project aims at optimal control, experimental wind-tunnel validation, and at including multi-disciplinary aspects, related to structural mechanics, power quality, and controller design.
Max ERC Funding
1 499 241 €
Duration
Start date: 2012-10-01, End date: 2017-09-30
Project acronym AEROSOL
Project Astrochemistry of old stars:direct probing of unique chemical laboratories
Researcher (PI) Leen Katrien Els Decin
Host Institution (HI) KATHOLIEKE UNIVERSITEIT LEUVEN
Call Details Consolidator Grant (CoG), PE9, ERC-2014-CoG
Summary The gas and dust in the interstellar medium (ISM) drive the chemical evolution of galaxies, the formation of stars and planets, and the synthesis of complex prebiotic molecules. The prime birth places for this interstellar material are the winds of evolved (super)giant stars. These winds are unique chemical laboratories, in which a large variety of gas and dust species radially expand away from the star.
Recent progress on the observations of these winds has been impressive thanks to Herschel and ALMA. The next challenge is to unravel the wealth of chemical information contained in these data. This is an ambitious task since (1) a plethora of physical and chemical processes interact in a complex way, (2) laboratory data to interpret these interactions are lacking, and (3) theoretical tools to analyse the data do not meet current needs.
To boost the knowledge of the physics and chemistry characterizing these winds, I propose a world-leading multi-disciplinary project combining (1) high-quality data, (2) novel theoretical wind models, and (3) targeted laboratory experiments. The aim is to pinpoint the dominant chemical pathways, unravel the transition from gas-phase to dust species, elucidate the role of clumps on the overall wind structure, and study the reciprocal effect between various dynamical and chemical phenomena.
Now is the right time for this ambitious project thanks to the availability of (1) high-quality multi-wavelength data, including ALMA and Herschel data of the PI, (2) supercomputers enabling a homogeneous analysis of the data using sophisticated theoretical wind models, and (3) novel laboratory equipment to measure the gas-phase reaction rates of key species.
This project will have far-reaching impact on (1) the field of evolved stars, (2) the understanding of the chemical lifecycle of the ISM, (3) chemical studies of dynamically more complex systems, such as exoplanets, protostars, supernovae etc., and (4) it will guide new instrument development.
Summary
The gas and dust in the interstellar medium (ISM) drive the chemical evolution of galaxies, the formation of stars and planets, and the synthesis of complex prebiotic molecules. The prime birth places for this interstellar material are the winds of evolved (super)giant stars. These winds are unique chemical laboratories, in which a large variety of gas and dust species radially expand away from the star.
Recent progress on the observations of these winds has been impressive thanks to Herschel and ALMA. The next challenge is to unravel the wealth of chemical information contained in these data. This is an ambitious task since (1) a plethora of physical and chemical processes interact in a complex way, (2) laboratory data to interpret these interactions are lacking, and (3) theoretical tools to analyse the data do not meet current needs.
To boost the knowledge of the physics and chemistry characterizing these winds, I propose a world-leading multi-disciplinary project combining (1) high-quality data, (2) novel theoretical wind models, and (3) targeted laboratory experiments. The aim is to pinpoint the dominant chemical pathways, unravel the transition from gas-phase to dust species, elucidate the role of clumps on the overall wind structure, and study the reciprocal effect between various dynamical and chemical phenomena.
Now is the right time for this ambitious project thanks to the availability of (1) high-quality multi-wavelength data, including ALMA and Herschel data of the PI, (2) supercomputers enabling a homogeneous analysis of the data using sophisticated theoretical wind models, and (3) novel laboratory equipment to measure the gas-phase reaction rates of key species.
This project will have far-reaching impact on (1) the field of evolved stars, (2) the understanding of the chemical lifecycle of the ISM, (3) chemical studies of dynamically more complex systems, such as exoplanets, protostars, supernovae etc., and (4) it will guide new instrument development.
Max ERC Funding
2 605 897 €
Duration
Start date: 2016-01-01, End date: 2020-12-31
Project acronym AEROSPACEPHYS
Project Multiphysics models and simulations for reacting and plasma flows applied to the space exploration program
Researcher (PI) Thierry Edouard Bertrand Magin
Host Institution (HI) INSTITUT VON KARMAN DE DYNAMIQUE DES FLUIDES
Call Details Starting Grant (StG), PE8, ERC-2010-StG_20091028
Summary Space exploration is one of boldest and most exciting endeavors that humanity has undertaken, and it holds enormous promise for the future. Our next challenges for the spatial conquest include bringing back samples to Earth by means of robotic missions and continuing the manned exploration program, which aims at sending human beings to Mars and bring them home safely. Inaccurate prediction of the heat-flux to the surface of the spacecraft heat shield can be fatal for the crew or the success of a robotic mission. This quantity is estimated during the design phase. An accurate prediction is a particularly complex task, regarding modelling of the following phenomena that are potential “mission killers:” 1) Radiation of the plasma in the shock layer, 2) Complex surface chemistry on the thermal protection material, 3) Flow transition from laminar to turbulent. Our poor understanding of the coupled mechanisms of radiation, ablation, and transition leads to the difficulties in flux prediction. To avoid failure and ensure safety of the astronauts and payload, engineers resort to “safety factors” to determine the thickness of the heat shield, at the expense of the mass of embarked payload. Thinking out of the box and basic research are thus necessary for advancements of the models that will better define the environment and requirements for the design and safe operation of tomorrow’s space vehicles and planetary probes for the manned space exploration. The three basic ingredients for predictive science are: 1) Physico-chemical models, 2) Computational methods, 3) Experimental data. We propose to follow a complementary approach for prediction. The proposed research aims at: “Integrating new advanced physico-chemical models and computational methods, based on a multidisciplinary approach developed together with physicists, chemists, and applied mathematicians, to create a top-notch multiphysics and multiscale numerical platform for simulations of planetary atmosphere entries, crucial to the new challenges of the manned space exploration program. Experimental data will also be used for validation, following state-of-the-art uncertainty quantification methods.”
Summary
Space exploration is one of boldest and most exciting endeavors that humanity has undertaken, and it holds enormous promise for the future. Our next challenges for the spatial conquest include bringing back samples to Earth by means of robotic missions and continuing the manned exploration program, which aims at sending human beings to Mars and bring them home safely. Inaccurate prediction of the heat-flux to the surface of the spacecraft heat shield can be fatal for the crew or the success of a robotic mission. This quantity is estimated during the design phase. An accurate prediction is a particularly complex task, regarding modelling of the following phenomena that are potential “mission killers:” 1) Radiation of the plasma in the shock layer, 2) Complex surface chemistry on the thermal protection material, 3) Flow transition from laminar to turbulent. Our poor understanding of the coupled mechanisms of radiation, ablation, and transition leads to the difficulties in flux prediction. To avoid failure and ensure safety of the astronauts and payload, engineers resort to “safety factors” to determine the thickness of the heat shield, at the expense of the mass of embarked payload. Thinking out of the box and basic research are thus necessary for advancements of the models that will better define the environment and requirements for the design and safe operation of tomorrow’s space vehicles and planetary probes for the manned space exploration. The three basic ingredients for predictive science are: 1) Physico-chemical models, 2) Computational methods, 3) Experimental data. We propose to follow a complementary approach for prediction. The proposed research aims at: “Integrating new advanced physico-chemical models and computational methods, based on a multidisciplinary approach developed together with physicists, chemists, and applied mathematicians, to create a top-notch multiphysics and multiscale numerical platform for simulations of planetary atmosphere entries, crucial to the new challenges of the manned space exploration program. Experimental data will also be used for validation, following state-of-the-art uncertainty quantification methods.”
Max ERC Funding
1 494 892 €
Duration
Start date: 2010-09-01, End date: 2015-08-31
Project acronym AFRIVAL
Project African river basins: catchment-scale carbon fluxes and transformations
Researcher (PI) Steven Bouillon
Host Institution (HI) KATHOLIEKE UNIVERSITEIT LEUVEN
Call Details Starting Grant (StG), PE10, ERC-2009-StG
Summary This proposal wishes to fundamentally improve our understanding of the role of tropical freshwater ecosystems in carbon (C) cycling on the catchment scale. It uses an unprecedented combination of state-of-the-art proxies such as stable isotope, 14C and biomarker signatures to characterize organic matter, radiogenic isotope signatures to determine particle residence times, as well as field measurements of relevant biogeochemical processes. We focus on tropical systems since there is a striking lack of data on such systems, even though riverine C transport is thought to be disproportionately high in tropical areas. Furthermore, the presence of landscape-scale contrasts in vegetation (in particular, C3 vs. C4 plants) are an important asset in the use of stable isotopes as natural tracers of C cycling processes on this scale. Freshwater ecosystems are an important component in the global C cycle, and the primary link between terrestrial and marine ecosystems. Recent estimates indicate that ~2 Pg C y-1 (Pg=Petagram) enter freshwater systems, i.e., about twice the estimated global terrestrial C sink. More than half of this is thought to be remineralized before it reaches the coastal zone, and for the Amazon basin this has even been suggested to be ~90% of the lateral C inputs. The question how general these patterns are is a matter of debate, and assessing the mechanisms determining the degree of processing versus transport of organic carbon in lakes and river systems is critical to further constrain their role in the global C cycle. This proposal provides an interdisciplinary approach to describe and quantify catchment-scale C transport and cycling in tropical river basins. Besides conceptual and methodological advances, and a significant expansion of our dataset on C processes in such systems, new data gathered in this project are likely to provide exciting and novel hypotheses on the functioning of freshwater systems and their linkage to the terrestrial C budget.
Summary
This proposal wishes to fundamentally improve our understanding of the role of tropical freshwater ecosystems in carbon (C) cycling on the catchment scale. It uses an unprecedented combination of state-of-the-art proxies such as stable isotope, 14C and biomarker signatures to characterize organic matter, radiogenic isotope signatures to determine particle residence times, as well as field measurements of relevant biogeochemical processes. We focus on tropical systems since there is a striking lack of data on such systems, even though riverine C transport is thought to be disproportionately high in tropical areas. Furthermore, the presence of landscape-scale contrasts in vegetation (in particular, C3 vs. C4 plants) are an important asset in the use of stable isotopes as natural tracers of C cycling processes on this scale. Freshwater ecosystems are an important component in the global C cycle, and the primary link between terrestrial and marine ecosystems. Recent estimates indicate that ~2 Pg C y-1 (Pg=Petagram) enter freshwater systems, i.e., about twice the estimated global terrestrial C sink. More than half of this is thought to be remineralized before it reaches the coastal zone, and for the Amazon basin this has even been suggested to be ~90% of the lateral C inputs. The question how general these patterns are is a matter of debate, and assessing the mechanisms determining the degree of processing versus transport of organic carbon in lakes and river systems is critical to further constrain their role in the global C cycle. This proposal provides an interdisciplinary approach to describe and quantify catchment-scale C transport and cycling in tropical river basins. Besides conceptual and methodological advances, and a significant expansion of our dataset on C processes in such systems, new data gathered in this project are likely to provide exciting and novel hypotheses on the functioning of freshwater systems and their linkage to the terrestrial C budget.
Max ERC Funding
1 745 262 €
Duration
Start date: 2009-10-01, End date: 2014-09-30
Project acronym ALUFIX
Project Friction stir processing based local damage mitigation and healing in aluminium alloys
Researcher (PI) Aude SIMAR
Host Institution (HI) UNIVERSITE CATHOLIQUE DE LOUVAIN
Call Details Starting Grant (StG), PE8, ERC-2016-STG
Summary ALUFIX proposes an original strategy for the development of aluminium-based materials involving damage mitigation and extrinsic self-healing concepts exploiting the new opportunities of the solid-state friction stir process. Friction stir processing locally extrudes and drags material from the front to the back and around the tool pin. It involves short duration at moderate temperatures (typically 80% of the melting temperature), fast cooling rates and large plastic deformations leading to far out-of-equilibrium microstructures. The idea is that commercial aluminium alloys can be locally improved and healed in regions of stress concentration where damage is likely to occur. Self-healing in metal-based materials is still in its infancy and existing strategies can hardly be extended to applications. Friction stir processing can enhance the damage and fatigue resistance of aluminium alloys by microstructure homogenisation and refinement. In parallel, friction stir processing can be used to integrate secondary phases in an aluminium matrix. In the ALUFIX project, healing phases will thus be integrated in aluminium in addition to refining and homogenising the microstructure. The “local stress management strategy” favours crack closure and crack deviation at the sub-millimetre scale thanks to a controlled residual stress field. The “transient liquid healing agent” strategy involves the in-situ generation of an out-of-equilibrium compositionally graded microstructure at the aluminium/healing agent interface capable of liquid-phase healing after a thermal treatment. Along the road, a variety of new scientific questions concerning the damage mechanisms will have to be addressed.
Summary
ALUFIX proposes an original strategy for the development of aluminium-based materials involving damage mitigation and extrinsic self-healing concepts exploiting the new opportunities of the solid-state friction stir process. Friction stir processing locally extrudes and drags material from the front to the back and around the tool pin. It involves short duration at moderate temperatures (typically 80% of the melting temperature), fast cooling rates and large plastic deformations leading to far out-of-equilibrium microstructures. The idea is that commercial aluminium alloys can be locally improved and healed in regions of stress concentration where damage is likely to occur. Self-healing in metal-based materials is still in its infancy and existing strategies can hardly be extended to applications. Friction stir processing can enhance the damage and fatigue resistance of aluminium alloys by microstructure homogenisation and refinement. In parallel, friction stir processing can be used to integrate secondary phases in an aluminium matrix. In the ALUFIX project, healing phases will thus be integrated in aluminium in addition to refining and homogenising the microstructure. The “local stress management strategy” favours crack closure and crack deviation at the sub-millimetre scale thanks to a controlled residual stress field. The “transient liquid healing agent” strategy involves the in-situ generation of an out-of-equilibrium compositionally graded microstructure at the aluminium/healing agent interface capable of liquid-phase healing after a thermal treatment. Along the road, a variety of new scientific questions concerning the damage mechanisms will have to be addressed.
Max ERC Funding
1 497 447 €
Duration
Start date: 2017-01-01, End date: 2021-12-31
Project acronym APOLLO
Project Advanced Signal Processing Technologies for Wireless Powered Communications
Researcher (PI) Ioannis Krikidis
Host Institution (HI) UNIVERSITY OF CYPRUS
Call Details Consolidator Grant (CoG), PE7, ERC-2018-COG
Summary Wireless power transfer (WPT), pioneered by Tesla, is an idea at least as old as radio communications. However, on the one hand, due to health concerns and the large antenna dimensions required for transmission of high energy levels, until recently WPT has been limited mostly to very short distance applications. On the other hand, recent advances in silicon technology have significantly reduced the energy needs of electronic systems, making WPT over radio waves a potential source of energy for low power devices. Although WPT through radio waves has already found various short-range applications (such as the radio-frequency identification technology, healthcare monitoring etc.), its integration as a building block in the operation of wireless communications systems is still unexploited. On the other hand, conventional radio wave based information and energy transmissions have largely been designed separately. However, many applications can benefit from simultaneous wireless information and power transfer (SWIPT).
The overall objective of the APOLLO project is to study the integration of WPT/SWIPT technology into future wireless communication systems. Compared to past and current research efforts in this area, our technical approach is deeply interdisciplinary and more comprehensive, combining the expertise of wireless communications, control theory, information theory, optimization, and electronics/microwave engineering.
The key outcomes of the project include: 1) a rigorous and complete mathematical theory for WPT/SWIPT via information/communication/control theoretic studies; 2) new physical and cross-layer mechanisms that will enable the integration of WPT/SWIPT into future communication systems; 3) new network architectures that will fully exploit potential benefits of WPT/SWIPT; and 4) development of a proof-of-concept by implementing highly-efficient and multi-band metamaterial energy harvesting sensors for SWIPT.
Summary
Wireless power transfer (WPT), pioneered by Tesla, is an idea at least as old as radio communications. However, on the one hand, due to health concerns and the large antenna dimensions required for transmission of high energy levels, until recently WPT has been limited mostly to very short distance applications. On the other hand, recent advances in silicon technology have significantly reduced the energy needs of electronic systems, making WPT over radio waves a potential source of energy for low power devices. Although WPT through radio waves has already found various short-range applications (such as the radio-frequency identification technology, healthcare monitoring etc.), its integration as a building block in the operation of wireless communications systems is still unexploited. On the other hand, conventional radio wave based information and energy transmissions have largely been designed separately. However, many applications can benefit from simultaneous wireless information and power transfer (SWIPT).
The overall objective of the APOLLO project is to study the integration of WPT/SWIPT technology into future wireless communication systems. Compared to past and current research efforts in this area, our technical approach is deeply interdisciplinary and more comprehensive, combining the expertise of wireless communications, control theory, information theory, optimization, and electronics/microwave engineering.
The key outcomes of the project include: 1) a rigorous and complete mathematical theory for WPT/SWIPT via information/communication/control theoretic studies; 2) new physical and cross-layer mechanisms that will enable the integration of WPT/SWIPT into future communication systems; 3) new network architectures that will fully exploit potential benefits of WPT/SWIPT; and 4) development of a proof-of-concept by implementing highly-efficient and multi-band metamaterial energy harvesting sensors for SWIPT.
Max ERC Funding
1 930 625 €
Duration
Start date: 2019-07-01, End date: 2024-06-30
Project acronym APOLs
Project Role of Apolipoproteins L in immunity and disease
Researcher (PI) Etienne Pays
Host Institution (HI) UNIVERSITE LIBRE DE BRUXELLES
Call Details Advanced Grant (AdG), LS6, ERC-2014-ADG
Summary Work conducted in my laboratory on the trypanosome killing factor of human serum led to the identification
of the primate-specific Apolipoprotein L1 (APOL1) as a novel pore-forming protein with striking similarities
with proteins of the apoptotic BCL2 family. APOL1 belongs to a family of proteins induced under
inflammatory conditions in myeloid and endothelial cells. APOL1 is efficiently neutralized by the SRA
protein of Trypanosoma rhodesiense, accounting for the ability of this trypanosome subspecies to infect
humans and cause sleeping sickness. We found that natural APOL1 variants escaping SRA neutralization and
therefore conferring human resistance to T. rhodesiense are associated with chronic kidney disease.
Moreover, transgenic mice expressing these APOL1 variants exhibit an obese phenotype. Our unpublished
results also indicate that APOLs control the lifespan of dendritic cells and podocytes activated by viral
stimuli. Therefore, we propose that the pathology of APOL variants is due to their deregulated activity on the
control of the cellular lifespan in myeloid/endothelial cells activated by pathogen detection.
This project aims at characterizing (i) the molecular mechanism by which APOLs control the lifespan of
activated dendritic cells and podocytes, which has direct impact on innate immunity and inflammation, and
(ii) the mechanism by which APOL1 variants cause pathology. In addition, we plan to detail the
physiological function of APOLs by studying the phenotype of transgenic mice either expressing human
APOL1 (wild-type and variants) or devoid of APOL genes, which we have recently generated. Finally, we
propose to exploit the extraordinary potential of trypanosomes for antigenic variation in order to produce
SRA variants able to neutralize the pathogenic APOL1 variants. Preliminary experiments suggest that in
podocytes SRA antagonizes APOL1 induction by viral stimulus and subsequent cell death, opening new
perspectives to treat kidney disease.
Summary
Work conducted in my laboratory on the trypanosome killing factor of human serum led to the identification
of the primate-specific Apolipoprotein L1 (APOL1) as a novel pore-forming protein with striking similarities
with proteins of the apoptotic BCL2 family. APOL1 belongs to a family of proteins induced under
inflammatory conditions in myeloid and endothelial cells. APOL1 is efficiently neutralized by the SRA
protein of Trypanosoma rhodesiense, accounting for the ability of this trypanosome subspecies to infect
humans and cause sleeping sickness. We found that natural APOL1 variants escaping SRA neutralization and
therefore conferring human resistance to T. rhodesiense are associated with chronic kidney disease.
Moreover, transgenic mice expressing these APOL1 variants exhibit an obese phenotype. Our unpublished
results also indicate that APOLs control the lifespan of dendritic cells and podocytes activated by viral
stimuli. Therefore, we propose that the pathology of APOL variants is due to their deregulated activity on the
control of the cellular lifespan in myeloid/endothelial cells activated by pathogen detection.
This project aims at characterizing (i) the molecular mechanism by which APOLs control the lifespan of
activated dendritic cells and podocytes, which has direct impact on innate immunity and inflammation, and
(ii) the mechanism by which APOL1 variants cause pathology. In addition, we plan to detail the
physiological function of APOLs by studying the phenotype of transgenic mice either expressing human
APOL1 (wild-type and variants) or devoid of APOL genes, which we have recently generated. Finally, we
propose to exploit the extraordinary potential of trypanosomes for antigenic variation in order to produce
SRA variants able to neutralize the pathogenic APOL1 variants. Preliminary experiments suggest that in
podocytes SRA antagonizes APOL1 induction by viral stimulus and subsequent cell death, opening new
perspectives to treat kidney disease.
Max ERC Funding
2 250 000 €
Duration
Start date: 2015-09-01, End date: 2020-08-31
Project acronym ASTHMACRYSTALCLEAR
Project Role of protein crystallization in type 2 immunity and asthma
Researcher (PI) Bart LAMBRECHT
Host Institution (HI) VIB
Call Details Advanced Grant (AdG), LS6, ERC-2017-ADG
Summary Spontaneous protein crystallization is a rare event in biology. Eosinophilic inflammation such as seen in the airways in asthma, chronic rhinosinusitis and helminth infection is however accompanied by accumulation of large amounts of extracellular Charcot-Leyden crystals. These are made of Galectin-10, a protein of unknown function produced by eosinophils, hallmark cells of type 2 immunity. In mice, eosinophilic inflammation is also accompanied by protein crystal build up, composed of the chitinase-like proteins Ym1 and Ym2, produced by alternatively activated macrophages. Here we challenge the current view that these crystals are just markers of eosinophil demise or macrophages activation. We hypothesize that protein crystallization serves an active role in immunoregulation of type 2 immunity. On the one hand, crystallization might turn a harmless protein into a danger signal. On the other hand, crystallization might sequester and eliminate the physiological function of soluble Galectin-10 and Ym1, or prolong it via slow release elution. For full understanding, we therefore need to understand the function of the proteins in a soluble and crystalline state. Our program at the frontline of immunology, molecular structural biology and clinical science combines innovative tool creation and integrative research to investigate the structure, function, and physiology of galectin-10 and related protein crystals. We chose to study asthma as the crystallizing proteins are abundantly present in human and murine disease. There is still a large medical need for novel therapies that could benefit patients with chronic steroid-resistant disease, and are alternatives to eosinophil-depleting antibodies whose long term effects are unknown.
Summary
Spontaneous protein crystallization is a rare event in biology. Eosinophilic inflammation such as seen in the airways in asthma, chronic rhinosinusitis and helminth infection is however accompanied by accumulation of large amounts of extracellular Charcot-Leyden crystals. These are made of Galectin-10, a protein of unknown function produced by eosinophils, hallmark cells of type 2 immunity. In mice, eosinophilic inflammation is also accompanied by protein crystal build up, composed of the chitinase-like proteins Ym1 and Ym2, produced by alternatively activated macrophages. Here we challenge the current view that these crystals are just markers of eosinophil demise or macrophages activation. We hypothesize that protein crystallization serves an active role in immunoregulation of type 2 immunity. On the one hand, crystallization might turn a harmless protein into a danger signal. On the other hand, crystallization might sequester and eliminate the physiological function of soluble Galectin-10 and Ym1, or prolong it via slow release elution. For full understanding, we therefore need to understand the function of the proteins in a soluble and crystalline state. Our program at the frontline of immunology, molecular structural biology and clinical science combines innovative tool creation and integrative research to investigate the structure, function, and physiology of galectin-10 and related protein crystals. We chose to study asthma as the crystallizing proteins are abundantly present in human and murine disease. There is still a large medical need for novel therapies that could benefit patients with chronic steroid-resistant disease, and are alternatives to eosinophil-depleting antibodies whose long term effects are unknown.
Max ERC Funding
2 499 846 €
Duration
Start date: 2018-08-01, End date: 2023-07-31
