Project acronym 14Constraint
Project Radiocarbon constraints for models of C cycling in terrestrial ecosystems: from process understanding to global benchmarking
Researcher (PI) Susan Trumbore
Host Institution (HI) MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Country Germany
Call Details Advanced Grant (AdG), PE10, ERC-2015-AdG
Summary The overall goal of 14Constraint is to enhance the availability and use of radiocarbon data as constraints for process-based understanding of the age distribution of carbon in and respired by soils and ecosystems. Carbon enters ecosystems by a single process, photosynthesis. It returns by a range of processes that depend on plant allocation and turnover, the efficiency and rate of litter decomposition and the mechanisms stabilizing C in soils. Thus the age distribution of respired CO2 and the age of C residing in plants, litter and soils are diagnostic properties of ecosystems that provide key constraints for testing carbon cycle models. Radiocarbon, especially the transit of ‘bomb’ 14C created in the 1960s, is a powerful tool for tracing C exchange on decadal to centennial timescales. 14Constraint will assemble a global database of existing radiocarbon data (WP1) and demonstrate how they can constrain and test ecosystem carbon cycle models. WP2 will fill data gaps and add new data from sites in key biomes that have ancillary data sufficient to construct belowground C and 14C budgets. These detailed investigations will focus on the role of time lags caused in necromass and fine roots, as well as the dynamics of deep soil C. Spatial extrapolation beyond the WP2 sites will require sampling along global gradients designed to explore the relative roles of mineralogy, vegetation and climate on the age of C in and respired from soil (WP3). Products of this 14Constraint will include the first publicly available global synthesis of terrestrial 14C data, and will add over 5000 new measurements. This project is urgently needed before atmospheric 14C levels decline to below 1950 levels as expected in the next decade.
Summary
The overall goal of 14Constraint is to enhance the availability and use of radiocarbon data as constraints for process-based understanding of the age distribution of carbon in and respired by soils and ecosystems. Carbon enters ecosystems by a single process, photosynthesis. It returns by a range of processes that depend on plant allocation and turnover, the efficiency and rate of litter decomposition and the mechanisms stabilizing C in soils. Thus the age distribution of respired CO2 and the age of C residing in plants, litter and soils are diagnostic properties of ecosystems that provide key constraints for testing carbon cycle models. Radiocarbon, especially the transit of ‘bomb’ 14C created in the 1960s, is a powerful tool for tracing C exchange on decadal to centennial timescales. 14Constraint will assemble a global database of existing radiocarbon data (WP1) and demonstrate how they can constrain and test ecosystem carbon cycle models. WP2 will fill data gaps and add new data from sites in key biomes that have ancillary data sufficient to construct belowground C and 14C budgets. These detailed investigations will focus on the role of time lags caused in necromass and fine roots, as well as the dynamics of deep soil C. Spatial extrapolation beyond the WP2 sites will require sampling along global gradients designed to explore the relative roles of mineralogy, vegetation and climate on the age of C in and respired from soil (WP3). Products of this 14Constraint will include the first publicly available global synthesis of terrestrial 14C data, and will add over 5000 new measurements. This project is urgently needed before atmospheric 14C levels decline to below 1950 levels as expected in the next decade.
Max ERC Funding
2 283 747 €
Duration
Start date: 2016-12-01, End date: 2021-11-30
Project acronym 2G-CSAFE
Project Combustion of Sustainable Alternative Fuels for Engines used in aeronautics and automotives
Researcher (PI) Philippe Dagaut
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Country France
Call Details Advanced Grant (AdG), PE8, ERC-2011-ADG_20110209
Summary This project aims at promoting sustainable combustion technologies for transport via validation of advanced combustion kinetic models obtained using sophisticated new laboratory experiments, engines, and theoretical computations, breaking through the current frontier of knowledge. It will focus on the unexplored kinetics of ignition and combustion of 2nd generation (2G) biofuels and blends with conventional fuels, which should provide energy safety and sustainability to Europe. The motivation is that no accurate kinetic models are available for the ignition, oxidation and combustion of 2G-biofuels, and improved ignition control is needed for new compression ignition engines. Crucial information is missing: data from well characterised experiments on combustion-generated pollutants and data on key-intermediates for fuels ignition in new engines.
To provide that knowledge new well-instrumented complementary experiments and kinetic modelling will be used. Measurements of key-intermediates, stables species, and pollutants will be performed. New ignition control strategies will be designed, opening new technological horizons. Kinetic modelling will be used for rationalising the results. Due to the complexity of 2G-biofuels and their unusual composition, innovative surrogates will be designed. Kinetic models for surrogate fuels will be generalised for extension to other compounds. The experimental results, together with ab-initio and detailed modelling, will serve to characterise the kinetics of ignition, combustion, and pollutants formation of fuels including 2G biofuels, and provide relevant data and models.
This research is risky because this is (i) the 1st effort to measure radicals by reactor/CRDS coupling, (ii) the 1st effort to use a μ-channel reactor to build ignition databases for conventional and bio-fuels, (iii) the 1st effort to design and use controlled generation and injection of reactive species to control ignition/combustion in compression ignition engines
Summary
This project aims at promoting sustainable combustion technologies for transport via validation of advanced combustion kinetic models obtained using sophisticated new laboratory experiments, engines, and theoretical computations, breaking through the current frontier of knowledge. It will focus on the unexplored kinetics of ignition and combustion of 2nd generation (2G) biofuels and blends with conventional fuels, which should provide energy safety and sustainability to Europe. The motivation is that no accurate kinetic models are available for the ignition, oxidation and combustion of 2G-biofuels, and improved ignition control is needed for new compression ignition engines. Crucial information is missing: data from well characterised experiments on combustion-generated pollutants and data on key-intermediates for fuels ignition in new engines.
To provide that knowledge new well-instrumented complementary experiments and kinetic modelling will be used. Measurements of key-intermediates, stables species, and pollutants will be performed. New ignition control strategies will be designed, opening new technological horizons. Kinetic modelling will be used for rationalising the results. Due to the complexity of 2G-biofuels and their unusual composition, innovative surrogates will be designed. Kinetic models for surrogate fuels will be generalised for extension to other compounds. The experimental results, together with ab-initio and detailed modelling, will serve to characterise the kinetics of ignition, combustion, and pollutants formation of fuels including 2G biofuels, and provide relevant data and models.
This research is risky because this is (i) the 1st effort to measure radicals by reactor/CRDS coupling, (ii) the 1st effort to use a μ-channel reactor to build ignition databases for conventional and bio-fuels, (iii) the 1st effort to design and use controlled generation and injection of reactive species to control ignition/combustion in compression ignition engines
Max ERC Funding
2 498 450 €
Duration
Start date: 2011-12-01, End date: 2016-11-30
Project acronym 3D-E
Project 3D Engineered Environments for Regenerative Medicine
Researcher (PI) Ruth Elizabeth Cameron
Host Institution (HI) THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE
Country United Kingdom
Call Details Advanced Grant (AdG), PE8, ERC-2012-ADG_20120216
Summary "This proposal develops a unified, underpinning technology to create novel, complex and biomimetic 3D environments for the control of tissue growth. As director of Cambridge Centre for Medical Materials, I have recently been approached by medical colleagues to help to solve important problems in the separate therapeutic areas of breast cancer, cardiac disease and blood disorders. In each case, the solution lies in complex 3D engineered environments for cell culture. These colleagues make it clear that existing 3D scaffolds fail to provide the required complex orientational and spatial anisotropy, and are limited in their ability to impart appropriate biochemical and mechanical cues.
I have a strong track record in this area. A particular success has been the use of a freeze drying technology to make collagen based porous implants for the cartilage-bone interface in the knee, which has now been commercialised. The novelty of this proposal lies in the broadening of the established scientific base of this technology to enable biomacromolecular structures with:
(A) controlled and complex pore orientation to mimic many normal multi-oriented tissue structures
(B) compositional and positional control to match varying local biochemical environments,
(C) the attachment of novel peptides designed to control cell behaviour, and
(D) mechanical control at both a local and macroscopic level to provide mechanical cues for cells.
These will be complemented by the development of
(E) robust characterisation methodologies for the structures created.
These advances will then be employed in each of the medical areas above.
This approach is highly interdisciplinary. Existing working relationships with experts in each medical field will guarantee expertise and licensed facilities in the required biological disciplines. Funds for this proposal would therefore establish a rich hub of mutually beneficial research and opportunities for cross-disciplinary sharing of expertise."
Summary
"This proposal develops a unified, underpinning technology to create novel, complex and biomimetic 3D environments for the control of tissue growth. As director of Cambridge Centre for Medical Materials, I have recently been approached by medical colleagues to help to solve important problems in the separate therapeutic areas of breast cancer, cardiac disease and blood disorders. In each case, the solution lies in complex 3D engineered environments for cell culture. These colleagues make it clear that existing 3D scaffolds fail to provide the required complex orientational and spatial anisotropy, and are limited in their ability to impart appropriate biochemical and mechanical cues.
I have a strong track record in this area. A particular success has been the use of a freeze drying technology to make collagen based porous implants for the cartilage-bone interface in the knee, which has now been commercialised. The novelty of this proposal lies in the broadening of the established scientific base of this technology to enable biomacromolecular structures with:
(A) controlled and complex pore orientation to mimic many normal multi-oriented tissue structures
(B) compositional and positional control to match varying local biochemical environments,
(C) the attachment of novel peptides designed to control cell behaviour, and
(D) mechanical control at both a local and macroscopic level to provide mechanical cues for cells.
These will be complemented by the development of
(E) robust characterisation methodologies for the structures created.
These advances will then be employed in each of the medical areas above.
This approach is highly interdisciplinary. Existing working relationships with experts in each medical field will guarantee expertise and licensed facilities in the required biological disciplines. Funds for this proposal would therefore establish a rich hub of mutually beneficial research and opportunities for cross-disciplinary sharing of expertise."
Max ERC Funding
2 486 267 €
Duration
Start date: 2013-04-01, End date: 2018-03-31
Project acronym 3DBrainStrom
Project Brain metastases: Deciphering tumor-stroma interactions in three dimensions for the rational design of nanomedicines
Researcher (PI) Ronit Satchi Fainaro
Host Institution (HI) TEL AVIV UNIVERSITY
Country Israel
Call Details Advanced Grant (AdG), LS7, ERC-2018-ADG
Summary Brain metastases represent a major therapeutic challenge. Despite significant breakthroughs in targeted therapies, survival rates of patients with brain metastases remain poor. Nowadays, discovery, development and evaluation of new therapies are performed on human cancer cells grown in 2D on rigid plastic plates followed by in vivo testing in immunodeficient mice. These experimental settings are lacking and constitute a fundamental hurdle for the translation of preclinical discoveries into clinical practice. We propose to establish 3D-printed models of brain metastases (Aim 1), which include brain extracellular matrix, stroma and serum containing immune cells flowing in functional tumor vessels. Our unique models better capture the clinical physio-mechanical tissue properties, signaling pathways, hemodynamics and drug responsiveness. Using our 3D-printed models, we aim to develop two new fronts for identifying novel clinically-relevant molecular drivers (Aim 2) followed by the development of precision nanomedicines (Aim 3). We will exploit our vast experience in anticancer nanomedicines to design three therapeutic approaches that target various cellular compartments involved in brain metastases: 1) Prevention of brain metastatic colonization using targeted nano-vaccines, which elicit antitumor immune response; 2) Intervention of tumor-brain stroma cells crosstalk when brain micrometastases establish; 3) Regression of macrometastatic disease by selectively targeting tumor cells. These approaches will materialize using our libraries of polymeric nanocarriers that selectively accumulate in tumors.
This project will result in a paradigm shift by generating new preclinical cancer models that will bridge the translational gap in cancer therapeutics. The insights and tumor-stroma-targeted nanomedicines developed here will pave the way for prediction of patient outcome, revolutionizing our perception of tumor modelling and consequently the way we prevent and treat cancer.
Summary
Brain metastases represent a major therapeutic challenge. Despite significant breakthroughs in targeted therapies, survival rates of patients with brain metastases remain poor. Nowadays, discovery, development and evaluation of new therapies are performed on human cancer cells grown in 2D on rigid plastic plates followed by in vivo testing in immunodeficient mice. These experimental settings are lacking and constitute a fundamental hurdle for the translation of preclinical discoveries into clinical practice. We propose to establish 3D-printed models of brain metastases (Aim 1), which include brain extracellular matrix, stroma and serum containing immune cells flowing in functional tumor vessels. Our unique models better capture the clinical physio-mechanical tissue properties, signaling pathways, hemodynamics and drug responsiveness. Using our 3D-printed models, we aim to develop two new fronts for identifying novel clinically-relevant molecular drivers (Aim 2) followed by the development of precision nanomedicines (Aim 3). We will exploit our vast experience in anticancer nanomedicines to design three therapeutic approaches that target various cellular compartments involved in brain metastases: 1) Prevention of brain metastatic colonization using targeted nano-vaccines, which elicit antitumor immune response; 2) Intervention of tumor-brain stroma cells crosstalk when brain micrometastases establish; 3) Regression of macrometastatic disease by selectively targeting tumor cells. These approaches will materialize using our libraries of polymeric nanocarriers that selectively accumulate in tumors.
This project will result in a paradigm shift by generating new preclinical cancer models that will bridge the translational gap in cancer therapeutics. The insights and tumor-stroma-targeted nanomedicines developed here will pave the way for prediction of patient outcome, revolutionizing our perception of tumor modelling and consequently the way we prevent and treat cancer.
Max ERC Funding
2 353 125 €
Duration
Start date: 2019-04-01, End date: 2024-03-31
Project acronym 4D-EEG
Project 4D-EEG: A new tool to investigate the spatial and temporal activity patterns in the brain
Researcher (PI) Franciscus C.T. Van Der Helm
Host Institution (HI) TECHNISCHE UNIVERSITEIT DELFT
Country Netherlands
Call Details Advanced Grant (AdG), PE7, ERC-2011-ADG_20110209
Summary Our first goal is to develop a new tool to determine brain activity with a high temporal (< 1 msec) and spatial (about 2 mm) resolution with the focus on motor control. High density EEG (up to 256 electrodes) will be used for EEG source localization. Advanced force-controlled robot manipulators will be used to impose continuous force perturbations to the joints. Advanced closed-loop system identification algorithms will identify the dynamic EEG response of multiple brain areas to the perturbation, leading to a functional interpretation of EEG. The propagation of the signal in time and 3D space through the cortex can be monitored: 4D-EEG. Preliminary experiments with EEG localization have shown that the continuous force perturbations resulted in a better signal-to-noise ratio and coherence than the current method using transient perturbations..
4D-EEG will be a direct measure of the neural activity in the brain with an excellent temporal response and easy to use in combination with motor control tasks. The new 4D-EEG method is expected to provide a breakthrough in comparison to functional MRI (fMRI) when elucidating the meaning of cortical map plasticity in motor learning.
Our second goal is to generate and validate new hypotheses about the longitudinal relationship between motor learning and cortical map plasticity by clinically using 4D-EEG in an intensive, repeated measurement design in patients suffering from a stroke. The application of 4D-EEG combined with haptic robots will allow us to discover how dynamics in cortical map plasticity are related with upper limb recovery after stroke in terms of neural repair and using behavioral compensation strategies while performing a meaningful motor tasks.. The non-invasive 4D-EEG technique combined with haptic robots will open the window about what and how patients (re)learn when showing motor recovery after stroke in order to allow us to develop more effective patient-tailored therapies in neuro-rehabilitation.
Summary
Our first goal is to develop a new tool to determine brain activity with a high temporal (< 1 msec) and spatial (about 2 mm) resolution with the focus on motor control. High density EEG (up to 256 electrodes) will be used for EEG source localization. Advanced force-controlled robot manipulators will be used to impose continuous force perturbations to the joints. Advanced closed-loop system identification algorithms will identify the dynamic EEG response of multiple brain areas to the perturbation, leading to a functional interpretation of EEG. The propagation of the signal in time and 3D space through the cortex can be monitored: 4D-EEG. Preliminary experiments with EEG localization have shown that the continuous force perturbations resulted in a better signal-to-noise ratio and coherence than the current method using transient perturbations..
4D-EEG will be a direct measure of the neural activity in the brain with an excellent temporal response and easy to use in combination with motor control tasks. The new 4D-EEG method is expected to provide a breakthrough in comparison to functional MRI (fMRI) when elucidating the meaning of cortical map plasticity in motor learning.
Our second goal is to generate and validate new hypotheses about the longitudinal relationship between motor learning and cortical map plasticity by clinically using 4D-EEG in an intensive, repeated measurement design in patients suffering from a stroke. The application of 4D-EEG combined with haptic robots will allow us to discover how dynamics in cortical map plasticity are related with upper limb recovery after stroke in terms of neural repair and using behavioral compensation strategies while performing a meaningful motor tasks.. The non-invasive 4D-EEG technique combined with haptic robots will open the window about what and how patients (re)learn when showing motor recovery after stroke in order to allow us to develop more effective patient-tailored therapies in neuro-rehabilitation.
Max ERC Funding
3 477 202 €
Duration
Start date: 2012-06-01, End date: 2017-05-31
Project acronym 4D-PET
Project Innovative PET scanner for dynamic imaging
Researcher (PI) Jose MarIa BENLLOCH BAVIERA
Host Institution (HI) AGENCIA ESTATAL CONSEJO SUPERIOR DEINVESTIGACIONES CIENTIFICAS
Country Spain
Call Details Advanced Grant (AdG), LS7, ERC-2015-AdG
Summary The main objective of 4D-PET is to develop an innovative whole-body PET scanner based in a new detector concept that stores 3D position and time of every single gamma interaction with unprecedented resolution. The combination of scanner geometrical design and high timing resolution will enable developing a full sequence of all gamma-ray interactions inside the scanner, including Compton interactions, like in a 3D movie. 4D-PET fully exploits Time Of Flight (TOF) information to obtain a better image quality and to increase scanner sensitivity, through the inclusion in the image formation of all Compton events occurring inside the detector, which are always rejected in state-of-the-art PET scanners. The new PET design will radically improve state-of-the-art PET performance features, overcoming limitations of current PET technology and opening up new diagnostic venues and very valuable physiological information
Summary
The main objective of 4D-PET is to develop an innovative whole-body PET scanner based in a new detector concept that stores 3D position and time of every single gamma interaction with unprecedented resolution. The combination of scanner geometrical design and high timing resolution will enable developing a full sequence of all gamma-ray interactions inside the scanner, including Compton interactions, like in a 3D movie. 4D-PET fully exploits Time Of Flight (TOF) information to obtain a better image quality and to increase scanner sensitivity, through the inclusion in the image formation of all Compton events occurring inside the detector, which are always rejected in state-of-the-art PET scanners. The new PET design will radically improve state-of-the-art PET performance features, overcoming limitations of current PET technology and opening up new diagnostic venues and very valuable physiological information
Max ERC Funding
2 048 386 €
Duration
Start date: 2017-01-01, End date: 2021-12-31
Project acronym 5D Heart Patch
Project A Functional, Mature In vivo Human Ventricular Muscle Patch for Cardiomyopathy
Researcher (PI) Kenneth Randall Chien
Host Institution (HI) KAROLINSKA INSTITUTET
Country Sweden
Call Details Advanced Grant (AdG), LS7, ERC-2016-ADG
Summary Developing new therapeutic strategies for heart regeneration is a major goal for cardiac biology and medicine. While cardiomyocytes can be generated from human pluripotent stem (hPSC) cells in vitro, it has proven difficult to use these cells to generate a large scale, mature human heart ventricular muscle graft on the injured heart in vivo. The central objective of this proposal is to optimize the generation of a large-scale pure, fully functional human ventricular muscle patch in vivo through the self-assembly of purified human ventricular progenitors and the localized expression of defined paracrine factors that drive their expansion, differentiation, vascularization, matrix formation, and maturation. Recently, we have found that purified hPSC-derived ventricular progenitors (HVPs) can self-assemble in vivo on the epicardial surface into a 3D vascularized, and functional ventricular patch with its own extracellular matrix via a cell autonomous pathway. A two-step protocol and FACS purification of HVP receptors can generate billions of pure HVPs- The current proposal will lead to the identification of defined paracrine pathways to enhance the survival, grafting/implantation, expansion, differentiation, matrix formation, vascularization and maturation of the graft in vivo. We will captalize on our unique HVP system and our novel modRNA technology to deliver therapeutic strategies by using the in vivo human ventricular muscle to model in vivo arrhythmogenic cardiomyopathy, and optimize the ability of the graft to compensate for the massive loss of functional muscle during ischemic cardiomyopathy and post-myocardial infarction. The studies will lead to new in vivo chimeric models of human cardiac disease and an experimental paradigm to optimize organ-on-organ cardiac tissue engineers of an in vivo, functional mature ventricular patch for cardiomyopathy
Summary
Developing new therapeutic strategies for heart regeneration is a major goal for cardiac biology and medicine. While cardiomyocytes can be generated from human pluripotent stem (hPSC) cells in vitro, it has proven difficult to use these cells to generate a large scale, mature human heart ventricular muscle graft on the injured heart in vivo. The central objective of this proposal is to optimize the generation of a large-scale pure, fully functional human ventricular muscle patch in vivo through the self-assembly of purified human ventricular progenitors and the localized expression of defined paracrine factors that drive their expansion, differentiation, vascularization, matrix formation, and maturation. Recently, we have found that purified hPSC-derived ventricular progenitors (HVPs) can self-assemble in vivo on the epicardial surface into a 3D vascularized, and functional ventricular patch with its own extracellular matrix via a cell autonomous pathway. A two-step protocol and FACS purification of HVP receptors can generate billions of pure HVPs- The current proposal will lead to the identification of defined paracrine pathways to enhance the survival, grafting/implantation, expansion, differentiation, matrix formation, vascularization and maturation of the graft in vivo. We will captalize on our unique HVP system and our novel modRNA technology to deliver therapeutic strategies by using the in vivo human ventricular muscle to model in vivo arrhythmogenic cardiomyopathy, and optimize the ability of the graft to compensate for the massive loss of functional muscle during ischemic cardiomyopathy and post-myocardial infarction. The studies will lead to new in vivo chimeric models of human cardiac disease and an experimental paradigm to optimize organ-on-organ cardiac tissue engineers of an in vivo, functional mature ventricular patch for cardiomyopathy
Max ERC Funding
2 149 228 €
Duration
Start date: 2017-12-01, End date: 2022-11-30
Project acronym A-DATADRIVE-B
Project Advanced Data-Driven Black-box modelling
Researcher (PI) Johan Adelia K Suykens
Host Institution (HI) KATHOLIEKE UNIVERSITEIT LEUVEN
Country Belgium
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 A2C2
Project Atmospheric flow Analogues and Climate Change
Researcher (PI) Pascal Yiou
Host Institution (HI) COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES
Country France
Call Details Advanced Grant (AdG), PE10, ERC-2013-ADG
Summary "The A2C2 project treats two major challenges in climate and atmospheric research: the time dependence of the climate attractor to external forcings (solar, volcanic eruptions and anthropogenic), and the attribution of extreme climate events occurring in the northern extra-tropics. The main difficulties are the limited climate information, the computer cost of model simulations, and mathematical assumptions that are hardly verified and often overlooked in the literature.
A2C2 proposes a practical framework to overcome those three difficulties, linking the theory of dynamical systems and statistics. We will generalize the methodology of flow analogues to multiple databases in order to obtain probabilistic descriptions of analogue decompositions.
The project is divided into three workpackages (WP). WP1 embeds the analogue method in the theory of dynamical systems in order to provide a metric of an attractor deformation in time. The important methodological step is to detect trends or persisting outliers in the dates and scores of analogues when the system yields time-varying forcings. This is done from idealized models and full size climate models in which the forcings (anthropogenic and natural) are known.
A2C2 creates an open source toolkit to compute flow analogues from a wide array of databases (WP2). WP3 treats the two scientific challenges with the analogue method and multiple model ensembles, hence allowing uncertainty estimates under realistic mathematical hypotheses. The flow analogue methodology allows a systematic and quasi real-time analysis of extreme events, which is currently out of the reach of conventional climate modeling approaches.
The major breakthrough of A2C2 is to bridge the gap between operational needs (the immediate analysis of climate events) and the understanding long-term climate changes. A2C2 opens new research horizons for the exploitation of ensembles of simulations and reliable estimates of uncertainty."
Summary
"The A2C2 project treats two major challenges in climate and atmospheric research: the time dependence of the climate attractor to external forcings (solar, volcanic eruptions and anthropogenic), and the attribution of extreme climate events occurring in the northern extra-tropics. The main difficulties are the limited climate information, the computer cost of model simulations, and mathematical assumptions that are hardly verified and often overlooked in the literature.
A2C2 proposes a practical framework to overcome those three difficulties, linking the theory of dynamical systems and statistics. We will generalize the methodology of flow analogues to multiple databases in order to obtain probabilistic descriptions of analogue decompositions.
The project is divided into three workpackages (WP). WP1 embeds the analogue method in the theory of dynamical systems in order to provide a metric of an attractor deformation in time. The important methodological step is to detect trends or persisting outliers in the dates and scores of analogues when the system yields time-varying forcings. This is done from idealized models and full size climate models in which the forcings (anthropogenic and natural) are known.
A2C2 creates an open source toolkit to compute flow analogues from a wide array of databases (WP2). WP3 treats the two scientific challenges with the analogue method and multiple model ensembles, hence allowing uncertainty estimates under realistic mathematical hypotheses. The flow analogue methodology allows a systematic and quasi real-time analysis of extreme events, which is currently out of the reach of conventional climate modeling approaches.
The major breakthrough of A2C2 is to bridge the gap between operational needs (the immediate analysis of climate events) and the understanding long-term climate changes. A2C2 opens new research horizons for the exploitation of ensembles of simulations and reliable estimates of uncertainty."
Max ERC Funding
1 491 457 €
Duration
Start date: 2014-03-01, End date: 2019-02-28
Project acronym AAA
Project Adaptive Actin Architectures
Researcher (PI) Laurent Blanchoin
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Country France
Call Details Advanced Grant (AdG), LS3, ERC-2016-ADG
Summary Although we have extensive knowledge of many important processes in cell biology, including information on many of the molecules involved and the physical interactions among them, we still do not understand most of the dynamical features that are the essence of living systems. This is particularly true for the actin cytoskeleton, a major component of the internal architecture of eukaryotic cells. In living cells, actin networks constantly assemble and disassemble filaments while maintaining an apparent stable structure, suggesting a perfect balance between the two processes. Such behaviors are called “dynamic steady states”. They confer upon actin networks a high degree of plasticity allowing them to adapt in response to external changes and enable cells to adjust to their environments. Despite their fundamental importance in the regulation of cell physiology, the basic mechanisms that control the coordinated dynamics of co-existing actin networks are poorly understood. In the AAA project, first, we will characterize the parameters that allow the coupling among co-existing actin networks at steady state. In vitro reconstituted systems will be used to control the actin nucleation patterns, the closed volume of the reaction chamber and the physical interaction of the networks. We hope to unravel the mechanism allowing the global coherence of a dynamic actin cytoskeleton. Second, we will use our unique capacity to perform dynamic micropatterning, to add or remove actin nucleation sites in real time, in order to investigate the ability of dynamic networks to adapt to changes and the role of coupled network dynamics in this emergent property. In this part, in vitro experiments will be complemented by the analysis of actin network remodeling in living cells. In the end, our project will provide a comprehensive understanding of how the adaptive response of the cytoskeleton derives from the complex interplay between its biochemical, structural and mechanical properties.
Summary
Although we have extensive knowledge of many important processes in cell biology, including information on many of the molecules involved and the physical interactions among them, we still do not understand most of the dynamical features that are the essence of living systems. This is particularly true for the actin cytoskeleton, a major component of the internal architecture of eukaryotic cells. In living cells, actin networks constantly assemble and disassemble filaments while maintaining an apparent stable structure, suggesting a perfect balance between the two processes. Such behaviors are called “dynamic steady states”. They confer upon actin networks a high degree of plasticity allowing them to adapt in response to external changes and enable cells to adjust to their environments. Despite their fundamental importance in the regulation of cell physiology, the basic mechanisms that control the coordinated dynamics of co-existing actin networks are poorly understood. In the AAA project, first, we will characterize the parameters that allow the coupling among co-existing actin networks at steady state. In vitro reconstituted systems will be used to control the actin nucleation patterns, the closed volume of the reaction chamber and the physical interaction of the networks. We hope to unravel the mechanism allowing the global coherence of a dynamic actin cytoskeleton. Second, we will use our unique capacity to perform dynamic micropatterning, to add or remove actin nucleation sites in real time, in order to investigate the ability of dynamic networks to adapt to changes and the role of coupled network dynamics in this emergent property. In this part, in vitro experiments will be complemented by the analysis of actin network remodeling in living cells. In the end, our project will provide a comprehensive understanding of how the adaptive response of the cytoskeleton derives from the complex interplay between its biochemical, structural and mechanical properties.
Max ERC Funding
2 349 898 €
Duration
Start date: 2017-09-01, End date: 2022-08-31
