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 ABEL
Project "Alpha-helical Barrels: Exploring, Understanding and Exploiting a New Class of Protein Structure"
Researcher (PI) Derek Neil Woolfson
Host Institution (HI) UNIVERSITY OF BRISTOL
Country United Kingdom
Call Details Advanced Grant (AdG), LS9, ERC-2013-ADG
Summary "Recently through de novo peptide design, we have discovered and presented a new protein structure. This is an all-parallel, 6-helix bundle with a continuous central channel of 0.5 – 0.6 nm diameter. We posit that this is one of a broader class of protein structures that we call the alpha-helical barrels. Here, in three Work Packages, we propose to explore these structures and to develop protein functions within them. First, through a combination of computer-aided design, peptide synthesis and thorough biophysical characterization, we will examine the extents and limits of the alpha-helical-barrel structures. Whilst this is curiosity driven research, it also has practical consequences for the studies that will follow; that is, alpha-helical barrels made from increasing numbers of helices have channels or pores that increase in a predictable way. Second, we will use rational and empirical design approaches to engineer a range of functions within these cavities, including binding capabilities and enzyme-like activities. Finally, and taking the programme into another ambitious area, we will use the alpha-helical barrels to template other folds that are otherwise difficult to design and engineer, notably beta-barrels that insert into membranes to render ion-channel and sensor functions."
Summary
"Recently through de novo peptide design, we have discovered and presented a new protein structure. This is an all-parallel, 6-helix bundle with a continuous central channel of 0.5 – 0.6 nm diameter. We posit that this is one of a broader class of protein structures that we call the alpha-helical barrels. Here, in three Work Packages, we propose to explore these structures and to develop protein functions within them. First, through a combination of computer-aided design, peptide synthesis and thorough biophysical characterization, we will examine the extents and limits of the alpha-helical-barrel structures. Whilst this is curiosity driven research, it also has practical consequences for the studies that will follow; that is, alpha-helical barrels made from increasing numbers of helices have channels or pores that increase in a predictable way. Second, we will use rational and empirical design approaches to engineer a range of functions within these cavities, including binding capabilities and enzyme-like activities. Finally, and taking the programme into another ambitious area, we will use the alpha-helical barrels to template other folds that are otherwise difficult to design and engineer, notably beta-barrels that insert into membranes to render ion-channel and sensor functions."
Max ERC Funding
2 467 844 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
Project acronym ACCLIMATE
Project Elucidating the Causes and Effects of Atlantic Circulation Changes through Model-Data Integration
Researcher (PI) Claire Waelbroeck
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Country France
Call Details Advanced Grant (AdG), PE10, ERC-2013-ADG
Summary Rapid changes in ocean circulation and climate have been observed in marine sediment and ice cores, notably over the last 60 thousand years (ky), highlighting the non-linear character of the climate system and underlining the possibility of rapid climate shifts in response to anthropogenic greenhouse gas forcing.
To date, these rapid changes in climate and ocean circulation are still not fully explained. Two main obstacles prevent going beyond the current state of knowledge:
- Paleoclimatic proxy data are by essence only indirect indicators of the climatic variables, and thus can not be directly compared with model outputs;
- A 4-D (latitude, longitude, water depth, time) reconstruction of Atlantic water masses over the past 40 ky is lacking: previous studies have generated isolated records with disparate timescales which do not allow the causes of circulation changes to be identified.
Overcoming these two major limitations will lead to major breakthroughs in climate research. Concretely, I will create the first database of Atlantic deep-sea records over the last 40 ky, and extract full climatic information from these records through an innovative model-data integration scheme using an isotopic proxy forward modeling approach. The novelty and exceptional potential of this scheme is twofold: (i) it avoids hypotheses on proxy interpretation and hence suppresses or strongly reduces the errors of interpretation of paleoclimatic records; (ii) it produces states of the climate system that best explain the observations over the last 40 ky, while being consistent with the model physics.
Expected results include:
• The elucidation of the mechanisms explaining rapid changes in ocean circulation and climate over the last 40 ky,
• Improved climate model physics and parameterizations,
• The first projections of future climate changes obtained with a model able to reproduce the highly non linear behavior of the climate system observed over the last 40 ky.
Summary
Rapid changes in ocean circulation and climate have been observed in marine sediment and ice cores, notably over the last 60 thousand years (ky), highlighting the non-linear character of the climate system and underlining the possibility of rapid climate shifts in response to anthropogenic greenhouse gas forcing.
To date, these rapid changes in climate and ocean circulation are still not fully explained. Two main obstacles prevent going beyond the current state of knowledge:
- Paleoclimatic proxy data are by essence only indirect indicators of the climatic variables, and thus can not be directly compared with model outputs;
- A 4-D (latitude, longitude, water depth, time) reconstruction of Atlantic water masses over the past 40 ky is lacking: previous studies have generated isolated records with disparate timescales which do not allow the causes of circulation changes to be identified.
Overcoming these two major limitations will lead to major breakthroughs in climate research. Concretely, I will create the first database of Atlantic deep-sea records over the last 40 ky, and extract full climatic information from these records through an innovative model-data integration scheme using an isotopic proxy forward modeling approach. The novelty and exceptional potential of this scheme is twofold: (i) it avoids hypotheses on proxy interpretation and hence suppresses or strongly reduces the errors of interpretation of paleoclimatic records; (ii) it produces states of the climate system that best explain the observations over the last 40 ky, while being consistent with the model physics.
Expected results include:
• The elucidation of the mechanisms explaining rapid changes in ocean circulation and climate over the last 40 ky,
• Improved climate model physics and parameterizations,
• The first projections of future climate changes obtained with a model able to reproduce the highly non linear behavior of the climate system observed over the last 40 ky.
Max ERC Funding
3 000 000 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
Project acronym ACRCC
Project Understanding the atmospheric circulation response to climate change
Researcher (PI) Theodore Shepherd
Host Institution (HI) THE UNIVERSITY OF READING
Country United Kingdom
Call Details Advanced Grant (AdG), PE10, ERC-2013-ADG
Summary Computer models based on known physical laws are our primary tool for predicting climate change. Yet the state-of-the-art models exhibit a disturbingly wide range of predictions of future climate change, especially when examined at the regional scale, which has not decreased as the models have become more comprehensive. The reasons for this are not understood. This represents a basic challenge to our fundamental understanding of climate.
The divergence of model projections is presumably related to systematic model errors in the large-scale fluxes of heat, moisture and momentum that control regional aspects of climate. That these errors stubbornly persist in spite of increases in the spatial resolution of the models suggests that they are associated with errors in the representation of unresolved processes, whose effects must be parameterised.
Most attention in climate science has hitherto focused on the thermodynamic aspects of climate. Dynamical aspects, which involve the atmospheric circulation, have received much less attention. However regional climate, including persistent climate regimes and extremes, is strongly controlled by atmospheric circulation patterns, which exhibit chaotic variability and whose representation in climate models depends sensitively on parameterised processes. Moreover the dynamical aspects of model projections are much less robust than the thermodynamic ones. There are good reasons to believe that model bias, the divergence of model projections, and chaotic variability are somehow related, although the relationships are not well understood. This calls for studying them together.
My proposed research will focus on this problem, addressing these three aspects of the atmospheric circulation response to climate change in parallel: (i) diagnosing the sources of model error; (ii) elucidating the relationship between model error and the spread in model projections; (iii) understanding the physical mechanisms of atmospheric variability.
Summary
Computer models based on known physical laws are our primary tool for predicting climate change. Yet the state-of-the-art models exhibit a disturbingly wide range of predictions of future climate change, especially when examined at the regional scale, which has not decreased as the models have become more comprehensive. The reasons for this are not understood. This represents a basic challenge to our fundamental understanding of climate.
The divergence of model projections is presumably related to systematic model errors in the large-scale fluxes of heat, moisture and momentum that control regional aspects of climate. That these errors stubbornly persist in spite of increases in the spatial resolution of the models suggests that they are associated with errors in the representation of unresolved processes, whose effects must be parameterised.
Most attention in climate science has hitherto focused on the thermodynamic aspects of climate. Dynamical aspects, which involve the atmospheric circulation, have received much less attention. However regional climate, including persistent climate regimes and extremes, is strongly controlled by atmospheric circulation patterns, which exhibit chaotic variability and whose representation in climate models depends sensitively on parameterised processes. Moreover the dynamical aspects of model projections are much less robust than the thermodynamic ones. There are good reasons to believe that model bias, the divergence of model projections, and chaotic variability are somehow related, although the relationships are not well understood. This calls for studying them together.
My proposed research will focus on this problem, addressing these three aspects of the atmospheric circulation response to climate change in parallel: (i) diagnosing the sources of model error; (ii) elucidating the relationship between model error and the spread in model projections; (iii) understanding the physical mechanisms of atmospheric variability.
Max ERC Funding
2 489 151 €
Duration
Start date: 2014-03-01, End date: 2020-02-29
Project acronym ACROSS
Project 3D Reconstruction and Modeling across Different Levels of Abstraction
Researcher (PI) Leif Kobbelt
Host Institution (HI) RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHEN
Country Germany
Call Details Advanced Grant (AdG), PE6, ERC-2013-ADG
Summary "Digital 3D models are gaining more and more importance in diverse application fields ranging from computer graphics, multimedia and simulation sciences to engineering, architecture, and medicine. Powerful technologies to digitize the 3D shape of real objects and scenes are becoming available even to consumers. However, the raw geometric data emerging from, e.g., 3D scanning or multi-view stereo often lacks a consistent structure and meta-information which are necessary for the effective deployment of such models in sophisticated down-stream applications like animation, simulation, or CAD/CAM that go beyond mere visualization. Our goal is to develop new fundamental algorithms which transform raw geometric input data into augmented 3D models that are equipped with structural meta information such as feature aligned meshes, patch segmentations, local and global geometric constraints, statistical shape variation data, or even procedural descriptions. Our methodological approach is inspired by the human perceptual system that integrates bottom-up (data-driven) and top-down (model-driven) mechanisms in its hierarchical processing. Similarly we combine algorithms operating on different levels of abstraction into reconstruction and modeling networks. Instead of developing an individual solution for each specific application scenario, we create an eco-system of algorithms for automatic processing and interactive design of highly complex 3D models. A key concept is the information flow across all levels of abstraction in a bottom-up as well as top-down fashion. We not only aim at optimizing geometric representations but in fact at bridging the gap between reconstruction and recognition of geometric objects. The results from this project will make it possible to bring 3D models of real world objects into many highly relevant applications in science, industry, and entertainment, greatly reducing the excessive manual effort that is still necessary today."
Summary
"Digital 3D models are gaining more and more importance in diverse application fields ranging from computer graphics, multimedia and simulation sciences to engineering, architecture, and medicine. Powerful technologies to digitize the 3D shape of real objects and scenes are becoming available even to consumers. However, the raw geometric data emerging from, e.g., 3D scanning or multi-view stereo often lacks a consistent structure and meta-information which are necessary for the effective deployment of such models in sophisticated down-stream applications like animation, simulation, or CAD/CAM that go beyond mere visualization. Our goal is to develop new fundamental algorithms which transform raw geometric input data into augmented 3D models that are equipped with structural meta information such as feature aligned meshes, patch segmentations, local and global geometric constraints, statistical shape variation data, or even procedural descriptions. Our methodological approach is inspired by the human perceptual system that integrates bottom-up (data-driven) and top-down (model-driven) mechanisms in its hierarchical processing. Similarly we combine algorithms operating on different levels of abstraction into reconstruction and modeling networks. Instead of developing an individual solution for each specific application scenario, we create an eco-system of algorithms for automatic processing and interactive design of highly complex 3D models. A key concept is the information flow across all levels of abstraction in a bottom-up as well as top-down fashion. We not only aim at optimizing geometric representations but in fact at bridging the gap between reconstruction and recognition of geometric objects. The results from this project will make it possible to bring 3D models of real world objects into many highly relevant applications in science, industry, and entertainment, greatly reducing the excessive manual effort that is still necessary today."
Max ERC Funding
2 482 000 €
Duration
Start date: 2014-03-01, End date: 2019-02-28
Project acronym ADOS
Project AMPA Receptor Dynamic Organization and Synaptic transmission in health and disease
Researcher (PI) Daniel Georges Gustave Choquet
Host Institution (HI) CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
Country France
Call Details Advanced Grant (AdG), LS5, ERC-2013-ADG
Summary AMPA glutamate receptors (AMPAR) play key roles in information processing by the brain as they mediate nearly all fast excitatory synaptic transmission. Their spatio-temporal organization in the post synapse with respect to presynaptic glutamate release sites is a key determinant in synaptic transmission. The activity-dependent regulation of AMPAR organization is at the heart of synaptic plasticity processes underlying learning and memory. Dysfunction of synaptic transmission - hence AMPAR organization - is likely at the origin of a number of brain diseases.
Building on discoveries made during my past ERC grant, our new ground-breaking objective is to uncover the mechanisms that link synaptic transmission with the dynamic organization of AMPAR and associated proteins. For this aim, we have assembled a team of neurobiologists, computer scientists and chemists with a track record of collaboration. We will combine physiology, cellular and molecular neurobiology with development of novel quantitative imaging and biomolecular tools to probe the molecular dynamics that regulate synaptic transmission.
Live high content 3D SuperResolution Light Imaging (SRLI) combined with electron microscopy will allow unprecedented visualization of AMPAR organization in synapses at the scale of individual subunits up to the level of intact tissue. Simultaneous SRLI and electrophysiology will elucidate the intricate relations between dynamic AMPAR organization, trafficking and synaptic transmission. Novel peptide- and small protein-based probes used as protein-protein interaction reporters and modulators will be developed to image and directly interfere with synapse organization.
We will identify new processes that are fundamental to activity dependent modifications of synaptic transmission. We will apply the above findings to understand the causes of early cognitive deficits in models of neurodegenerative disorders and open new avenues of research for innovative therapies.
Summary
AMPA glutamate receptors (AMPAR) play key roles in information processing by the brain as they mediate nearly all fast excitatory synaptic transmission. Their spatio-temporal organization in the post synapse with respect to presynaptic glutamate release sites is a key determinant in synaptic transmission. The activity-dependent regulation of AMPAR organization is at the heart of synaptic plasticity processes underlying learning and memory. Dysfunction of synaptic transmission - hence AMPAR organization - is likely at the origin of a number of brain diseases.
Building on discoveries made during my past ERC grant, our new ground-breaking objective is to uncover the mechanisms that link synaptic transmission with the dynamic organization of AMPAR and associated proteins. For this aim, we have assembled a team of neurobiologists, computer scientists and chemists with a track record of collaboration. We will combine physiology, cellular and molecular neurobiology with development of novel quantitative imaging and biomolecular tools to probe the molecular dynamics that regulate synaptic transmission.
Live high content 3D SuperResolution Light Imaging (SRLI) combined with electron microscopy will allow unprecedented visualization of AMPAR organization in synapses at the scale of individual subunits up to the level of intact tissue. Simultaneous SRLI and electrophysiology will elucidate the intricate relations between dynamic AMPAR organization, trafficking and synaptic transmission. Novel peptide- and small protein-based probes used as protein-protein interaction reporters and modulators will be developed to image and directly interfere with synapse organization.
We will identify new processes that are fundamental to activity dependent modifications of synaptic transmission. We will apply the above findings to understand the causes of early cognitive deficits in models of neurodegenerative disorders and open new avenues of research for innovative therapies.
Max ERC Funding
2 491 157 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
Project acronym ADREEM
Project Adding Another Dimension – Arrays of 3D Bio-Responsive Materials
Researcher (PI) Mark Bradley
Host Institution (HI) THE UNIVERSITY OF EDINBURGH
Country United Kingdom
Call Details Advanced Grant (AdG), LS9, ERC-2013-ADG
Summary This proposal is focused in the areas of chemical medicine and chemical biology with the key drivers being the discovery and development of new materials that have practical functionality and application. The project will enable the fabrication of thousands of three-dimensional “smart-polymers” that will allow: (i). The precise and controlled release of drugs upon the addition of either a small molecule trigger or in response to disease, (ii). The discovery of materials that control and manipulate cells with the identification of scaffolds that provide the necessary biochemical cues for directing cell fate and drive tissue regeneration and (iii). The development of new classes of “smart-polymers” able, in real-time, to sense and report bacterial contamination. The newly discovered materials will find multiple biomedical applications in regenerative medicine and biotechnology ranging from 3D cell culture, bone repair and niche stabilisation to bacterial sensing/removal, while offering a new paradigm in drug delivery with biomarker triggered drug release.
Summary
This proposal is focused in the areas of chemical medicine and chemical biology with the key drivers being the discovery and development of new materials that have practical functionality and application. The project will enable the fabrication of thousands of three-dimensional “smart-polymers” that will allow: (i). The precise and controlled release of drugs upon the addition of either a small molecule trigger or in response to disease, (ii). The discovery of materials that control and manipulate cells with the identification of scaffolds that provide the necessary biochemical cues for directing cell fate and drive tissue regeneration and (iii). The development of new classes of “smart-polymers” able, in real-time, to sense and report bacterial contamination. The newly discovered materials will find multiple biomedical applications in regenerative medicine and biotechnology ranging from 3D cell culture, bone repair and niche stabilisation to bacterial sensing/removal, while offering a new paradigm in drug delivery with biomarker triggered drug release.
Max ERC Funding
2 310 884 €
Duration
Start date: 2014-11-01, End date: 2019-10-31
Project acronym ALEM
Project ADDITIONAL LOSSES IN ELECTRICAL MACHINES
Researcher (PI) Matti Antero Arkkio
Host Institution (HI) AALTO KORKEAKOULUSAATIO SR
Country Finland
Call Details Advanced Grant (AdG), PE8, ERC-2013-ADG
Summary "Electrical motors consume about 40 % of the electrical energy produced in the European Union. About 90 % of this energy is converted to mechanical work. However, 0.5-2.5 % of it goes to so called additional load losses whose exact origins are unknown. Our ambitious aim is to reveal the origins of these losses, build up numerical tools for modeling them and optimize electrical motors to minimize the losses.
As the hypothesis of the research, we assume that the additional losses mainly result from the deterioration of the core materials during the manufacturing process of the machine. By calorimetric measurements, we have found that the core losses of electrical machines may be twice as large as comprehensive loss models predict. The electrical steel sheets are punched, welded together and shrink fit to the frame. This causes residual strains in the core sheets deteriorating their magnetic characteristics. The cutting burrs make galvanic contacts between the sheets and form paths for inter-lamination currents. Another potential source of additional losses are the circulating currents between the parallel strands of random-wound armature windings. The stochastic nature of these potential sources of additional losses puts more challenge on the research.
We shall develop a physical loss model that couples the mechanical strains and electromagnetic losses in electrical steel sheets and apply the new model for comprehensive loss analysis of electrical machines. The stochastic variables related to the core losses and circulating-current losses will be discretized together with the temporal and spatial discretization of the electromechanical field variables. The numerical stochastic loss model will be used to search for such machine constructions that are insensitive to the manufacturing defects. We shall validate the new numerical loss models by electromechanical and calorimetric measurements."
Summary
"Electrical motors consume about 40 % of the electrical energy produced in the European Union. About 90 % of this energy is converted to mechanical work. However, 0.5-2.5 % of it goes to so called additional load losses whose exact origins are unknown. Our ambitious aim is to reveal the origins of these losses, build up numerical tools for modeling them and optimize electrical motors to minimize the losses.
As the hypothesis of the research, we assume that the additional losses mainly result from the deterioration of the core materials during the manufacturing process of the machine. By calorimetric measurements, we have found that the core losses of electrical machines may be twice as large as comprehensive loss models predict. The electrical steel sheets are punched, welded together and shrink fit to the frame. This causes residual strains in the core sheets deteriorating their magnetic characteristics. The cutting burrs make galvanic contacts between the sheets and form paths for inter-lamination currents. Another potential source of additional losses are the circulating currents between the parallel strands of random-wound armature windings. The stochastic nature of these potential sources of additional losses puts more challenge on the research.
We shall develop a physical loss model that couples the mechanical strains and electromagnetic losses in electrical steel sheets and apply the new model for comprehensive loss analysis of electrical machines. The stochastic variables related to the core losses and circulating-current losses will be discretized together with the temporal and spatial discretization of the electromechanical field variables. The numerical stochastic loss model will be used to search for such machine constructions that are insensitive to the manufacturing defects. We shall validate the new numerical loss models by electromechanical and calorimetric measurements."
Max ERC Funding
2 489 949 €
Duration
Start date: 2014-03-01, End date: 2019-02-28
Project acronym ALEXANDRIA
Project "Foundations for Temporal Retrieval, Exploration and Analytics in Web Archives"
Researcher (PI) Wolfgang Nejdl
Host Institution (HI) GOTTFRIED WILHELM LEIBNIZ UNIVERSITAET HANNOVER
Country Germany
Call Details Advanced Grant (AdG), PE6, ERC-2013-ADG
Summary "Significant parts of our cultural heritage are produced on the Web, yet only insufficient opportunities exist for accessing and exploring the past of the Web. The ALEXANDRIA project aims to develop models, tools and techniques necessary to archive and index relevant parts of the Web, and to retrieve and explore this information in a meaningful way. While the easy accessibility to the current Web is a good baseline, optimal access to Web archives requires new models and algorithms for retrieval, exploration, and analytics which go far beyond what is needed to access the current state of the Web. This includes taking into account the unique temporal dimension of Web archives, structured semantic information already available on the Web, as well as social media and network information.
Within ALEXANDRIA, we will significantly advance semantic and time-based indexing for Web archives using human-compiled knowledge available on the Web, to efficiently index, retrieve and explore information about entities and events from the past. In doing so, we will focus on the concurrent evolution of this knowledge and the Web content to be indexed, and take into account diversity and incompleteness of this knowledge. We will further investigate mixed crowd- and machine-based Web analytics to support long- running and collaborative retrieval and analysis processes on Web archives. Usage of implicit human feedback will be essential to provide better indexing through insights during the analysis process and to better focus harvesting of content.
The ALEXANDRIA Testbed will provide an important context for research, exploration and evaluation of the concepts, methods and algorithms developed in this project, and will provide both relevant collections and algorithms that enable further research on and practical application of our research results to existing archives like the Internet Archive, the Internet Memory Foundation and Web archives maintained by European national libraries."
Summary
"Significant parts of our cultural heritage are produced on the Web, yet only insufficient opportunities exist for accessing and exploring the past of the Web. The ALEXANDRIA project aims to develop models, tools and techniques necessary to archive and index relevant parts of the Web, and to retrieve and explore this information in a meaningful way. While the easy accessibility to the current Web is a good baseline, optimal access to Web archives requires new models and algorithms for retrieval, exploration, and analytics which go far beyond what is needed to access the current state of the Web. This includes taking into account the unique temporal dimension of Web archives, structured semantic information already available on the Web, as well as social media and network information.
Within ALEXANDRIA, we will significantly advance semantic and time-based indexing for Web archives using human-compiled knowledge available on the Web, to efficiently index, retrieve and explore information about entities and events from the past. In doing so, we will focus on the concurrent evolution of this knowledge and the Web content to be indexed, and take into account diversity and incompleteness of this knowledge. We will further investigate mixed crowd- and machine-based Web analytics to support long- running and collaborative retrieval and analysis processes on Web archives. Usage of implicit human feedback will be essential to provide better indexing through insights during the analysis process and to better focus harvesting of content.
The ALEXANDRIA Testbed will provide an important context for research, exploration and evaluation of the concepts, methods and algorithms developed in this project, and will provide both relevant collections and algorithms that enable further research on and practical application of our research results to existing archives like the Internet Archive, the Internet Memory Foundation and Web archives maintained by European national libraries."
Max ERC Funding
2 493 600 €
Duration
Start date: 2014-03-01, End date: 2019-02-28
Project acronym AMAIZE
Project Atlas of leaf growth regulatory networks in MAIZE
Researcher (PI) Dirk, Gustaaf Inze
Host Institution (HI) VIB VZW
Country Belgium
Call Details Advanced Grant (AdG), LS9, ERC-2013-ADG
Summary "Understanding how organisms regulate size is one of the most fascinating open questions in biology. The aim of the AMAIZE project is to unravel how growth of maize leaves is controlled. Maize leaf development offers great opportunities to study the dynamics of growth regulatory networks, essentially because leaf development is a linear system with cell division at the leaf basis followed by cell expansion and maturation. Furthermore, the growth zone is relatively large allowing easy access of tissues at different positions. Four different perturbations of maize leaf size will be analyzed with cellular resolution: wild-type and plants having larger leaves (as a consequence of GA20OX1 overexpression), both grown under either well-watered or mild drought conditions. Firstly, a 3D cellular map of the growth zone of the fourth leaf will be made. RNA-SEQ of three different tissues (adaxial- and abaxial epidermis; mesophyll) obtained by laser dissection with an interval of 2.5 mm along the growth zone will allow for the analysis of the transcriptome with high resolution. Additionally, the composition of fifty selected growth regulatory protein complexes and DNA targets of transcription factors will be determined with an interval of 5 mm along the growth zone. Computational methods will be used to construct comprehensive integrative maps of the cellular and molecular processes occurring along the growth zone. Finally, selected regulatory nodes of the growth regulatory networks will be further functionally analyzed using a transactivation system in maize.
AMAIZE opens up new perspectives for the identification of optimal growth regulatory networks that can be selected for by advanced breeding or for which more robust variants (e.g. reduced susceptibility to drought) can be obtained through genetic engineering. The ability to improve the growth of maize and in analogy other cereals could have a high impact in providing food security"
Summary
"Understanding how organisms regulate size is one of the most fascinating open questions in biology. The aim of the AMAIZE project is to unravel how growth of maize leaves is controlled. Maize leaf development offers great opportunities to study the dynamics of growth regulatory networks, essentially because leaf development is a linear system with cell division at the leaf basis followed by cell expansion and maturation. Furthermore, the growth zone is relatively large allowing easy access of tissues at different positions. Four different perturbations of maize leaf size will be analyzed with cellular resolution: wild-type and plants having larger leaves (as a consequence of GA20OX1 overexpression), both grown under either well-watered or mild drought conditions. Firstly, a 3D cellular map of the growth zone of the fourth leaf will be made. RNA-SEQ of three different tissues (adaxial- and abaxial epidermis; mesophyll) obtained by laser dissection with an interval of 2.5 mm along the growth zone will allow for the analysis of the transcriptome with high resolution. Additionally, the composition of fifty selected growth regulatory protein complexes and DNA targets of transcription factors will be determined with an interval of 5 mm along the growth zone. Computational methods will be used to construct comprehensive integrative maps of the cellular and molecular processes occurring along the growth zone. Finally, selected regulatory nodes of the growth regulatory networks will be further functionally analyzed using a transactivation system in maize.
AMAIZE opens up new perspectives for the identification of optimal growth regulatory networks that can be selected for by advanced breeding or for which more robust variants (e.g. reduced susceptibility to drought) can be obtained through genetic engineering. The ability to improve the growth of maize and in analogy other cereals could have a high impact in providing food security"
Max ERC Funding
2 418 429 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
