Project acronym 2D-CHEM
Project Two-Dimensional Chemistry towards New Graphene Derivatives
Researcher (PI) Michal Otyepka
Host Institution (HI) UNIVERZITA PALACKEHO V OLOMOUCI
Country Czechia
Call Details Consolidator Grant (CoG), PE5, ERC-2015-CoG
Summary The suite of graphene’s unique properties and applications can be enormously enhanced by its functionalization. As non-covalently functionalized graphenes do not target all graphene’s properties and may suffer from limited stability, covalent functionalization represents a promising way for controlling graphene’s properties. To date, only a few well-defined graphene derivatives have been introduced. Among them, fluorographene (FG) stands out as a prominent member because of its easy synthesis and high stability. Being a perfluorinated hydrocarbon, FG was believed to be as unreactive as the two-dimensional counterpart perfluoropolyethylene (Teflon®). However, our recent experiments showed that FG is not chemically inert and can be used as a viable precursor for synthesizing graphene derivatives. This surprising behavior indicates that common textbook grade knowledge cannot blindly be applied to the chemistry of 2D materials. Further, there might be specific rules behind the chemistry of 2D materials, forming a new chemical discipline we tentatively call 2D chemistry. The main aim of the project is to explore, identify and apply the rules of 2D chemistry starting from FG. Using the knowledge gained of 2D chemistry, we will attempt to control the chemistry of various 2D materials aimed at preparing stable graphene derivatives with designed properties, e.g., 1-3 eV band gap, fluorescent properties, sustainable magnetic ordering and dispersability in polar media. The new graphene derivatives will be applied in sensing, imaging, magnetic delivery and catalysis and new emerging applications arising from the synergistic phenomena are expected. We envisage that new applications will be opened up that benefit from the 2D scaffold and tailored properties of the synthesized derivatives. The derivatives will be used for the synthesis of 3D hybrid materials by covalent linking of the 2D sheets joined with other organic and inorganic molecules, nanomaterials or biomacromolecules.
Summary
The suite of graphene’s unique properties and applications can be enormously enhanced by its functionalization. As non-covalently functionalized graphenes do not target all graphene’s properties and may suffer from limited stability, covalent functionalization represents a promising way for controlling graphene’s properties. To date, only a few well-defined graphene derivatives have been introduced. Among them, fluorographene (FG) stands out as a prominent member because of its easy synthesis and high stability. Being a perfluorinated hydrocarbon, FG was believed to be as unreactive as the two-dimensional counterpart perfluoropolyethylene (Teflon®). However, our recent experiments showed that FG is not chemically inert and can be used as a viable precursor for synthesizing graphene derivatives. This surprising behavior indicates that common textbook grade knowledge cannot blindly be applied to the chemistry of 2D materials. Further, there might be specific rules behind the chemistry of 2D materials, forming a new chemical discipline we tentatively call 2D chemistry. The main aim of the project is to explore, identify and apply the rules of 2D chemistry starting from FG. Using the knowledge gained of 2D chemistry, we will attempt to control the chemistry of various 2D materials aimed at preparing stable graphene derivatives with designed properties, e.g., 1-3 eV band gap, fluorescent properties, sustainable magnetic ordering and dispersability in polar media. The new graphene derivatives will be applied in sensing, imaging, magnetic delivery and catalysis and new emerging applications arising from the synergistic phenomena are expected. We envisage that new applications will be opened up that benefit from the 2D scaffold and tailored properties of the synthesized derivatives. The derivatives will be used for the synthesis of 3D hybrid materials by covalent linking of the 2D sheets joined with other organic and inorganic molecules, nanomaterials or biomacromolecules.
Max ERC Funding
1 831 103 €
Duration
Start date: 2016-06-01, End date: 2021-05-31
Project acronym 3D Reloaded
Project 3D Reloaded: Novel Algorithms for 3D Shape Inference and Analysis
Researcher (PI) Daniel Cremers
Host Institution (HI) TECHNISCHE UNIVERSITAET MUENCHEN
Country Germany
Call Details Consolidator Grant (CoG), PE6, ERC-2014-CoG
Summary Despite their amazing success, we believe that computer vision algorithms have only scratched the surface of what can be done in terms of modeling and understanding our world from images. We believe that novel image analysis techniques will be a major enabler and driving force behind next-generation technologies, enhancing everyday life and opening up radically new possibilities. And we believe that the key to achieving this is to develop algorithms for reconstructing and analyzing the 3D structure of our world.
In this project, we will focus on three lines of research:
A) We will develop algorithms for 3D reconstruction from standard color cameras and from RGB-D cameras. In particular, we will promote real-time-capable direct and dense methods. In contrast to the classical two-stage approach of sparse feature-point based motion estimation and subsequent dense reconstruction, these methods optimally exploit all color information to jointly estimate dense geometry and camera motion.
B) We will develop algorithms for 3D shape analysis, including rigid and non-rigid matching, decomposition and interpretation of 3D shapes. We will focus on algorithms which are optimal or near-optimal. One of the major computational challenges lies in generalizing existing 2D shape analysis techniques to shapes in 3D and 4D (temporal evolutions of 3D shape).
C) We will develop shape priors for 3D reconstruction. These can be learned from sample shapes or acquired during the reconstruction process. For example, when reconstructing a larger office algorithms may exploit the geometric self-similarity of the scene, storing a model of a chair and its multiple instances only once rather than multiple times.
Advancing the state of the art in geometric reconstruction and geometric analysis will have a profound impact well beyond computer vision. We strongly believe that we have the necessary competence to pursue this project. Preliminary results have been well received by the community.
Summary
Despite their amazing success, we believe that computer vision algorithms have only scratched the surface of what can be done in terms of modeling and understanding our world from images. We believe that novel image analysis techniques will be a major enabler and driving force behind next-generation technologies, enhancing everyday life and opening up radically new possibilities. And we believe that the key to achieving this is to develop algorithms for reconstructing and analyzing the 3D structure of our world.
In this project, we will focus on three lines of research:
A) We will develop algorithms for 3D reconstruction from standard color cameras and from RGB-D cameras. In particular, we will promote real-time-capable direct and dense methods. In contrast to the classical two-stage approach of sparse feature-point based motion estimation and subsequent dense reconstruction, these methods optimally exploit all color information to jointly estimate dense geometry and camera motion.
B) We will develop algorithms for 3D shape analysis, including rigid and non-rigid matching, decomposition and interpretation of 3D shapes. We will focus on algorithms which are optimal or near-optimal. One of the major computational challenges lies in generalizing existing 2D shape analysis techniques to shapes in 3D and 4D (temporal evolutions of 3D shape).
C) We will develop shape priors for 3D reconstruction. These can be learned from sample shapes or acquired during the reconstruction process. For example, when reconstructing a larger office algorithms may exploit the geometric self-similarity of the scene, storing a model of a chair and its multiple instances only once rather than multiple times.
Advancing the state of the art in geometric reconstruction and geometric analysis will have a profound impact well beyond computer vision. We strongly believe that we have the necessary competence to pursue this project. Preliminary results have been well received by the community.
Max ERC Funding
2 000 000 €
Duration
Start date: 2015-09-01, End date: 2020-08-31
Project acronym 3D-REPAIR
Project Spatial organization of DNA repair within the nucleus
Researcher (PI) Evanthia Soutoglou
Host Institution (HI) THE UNIVERSITY OF SUSSEX
Country United Kingdom
Call Details Consolidator Grant (CoG), LS2, ERC-2015-CoG
Summary Faithful repair of double stranded DNA breaks (DSBs) is essential, as they are at the origin of genome instability, chromosomal translocations and cancer. Cells repair DSBs through different pathways, which can be faithful or mutagenic, and the balance between them at a given locus must be tightly regulated to preserve genome integrity. Although, much is known about DSB repair factors, how the choice between pathways is controlled within the nuclear environment is not understood. We have shown that nuclear architecture and non-random genome organization determine the frequency of chromosomal translocations and that pathway choice is dictated by the spatial organization of DNA in the nucleus. Nevertheless, what determines which pathway is activated in response to DSBs at specific genomic locations is not understood. Furthermore, the impact of 3D-genome folding on the kinetics and efficiency of DSB repair is completely unknown.
Here we aim to understand how nuclear compartmentalization, chromatin structure and genome organization impact on the efficiency of detection, signaling and repair of DSBs. We will unravel what determines the DNA repair specificity within distinct nuclear compartments using protein tethering, promiscuous biotinylation and quantitative proteomics. We will determine how DNA repair is orchestrated at different heterochromatin structures using a CRISPR/Cas9-based system that allows, for the first time robust induction of DSBs at specific heterochromatin compartments. Finally, we will investigate the role of 3D-genome folding in the kinetics of DNA repair and pathway choice using single nucleotide resolution DSB-mapping coupled to 3D-topological maps.
This proposal has significant implications for understanding the mechanisms controlling DNA repair within the nuclear environment and will reveal the regions of the genome that are susceptible to genomic instability and help us understand why certain mutations and translocations are recurrent in cancer
Summary
Faithful repair of double stranded DNA breaks (DSBs) is essential, as they are at the origin of genome instability, chromosomal translocations and cancer. Cells repair DSBs through different pathways, which can be faithful or mutagenic, and the balance between them at a given locus must be tightly regulated to preserve genome integrity. Although, much is known about DSB repair factors, how the choice between pathways is controlled within the nuclear environment is not understood. We have shown that nuclear architecture and non-random genome organization determine the frequency of chromosomal translocations and that pathway choice is dictated by the spatial organization of DNA in the nucleus. Nevertheless, what determines which pathway is activated in response to DSBs at specific genomic locations is not understood. Furthermore, the impact of 3D-genome folding on the kinetics and efficiency of DSB repair is completely unknown.
Here we aim to understand how nuclear compartmentalization, chromatin structure and genome organization impact on the efficiency of detection, signaling and repair of DSBs. We will unravel what determines the DNA repair specificity within distinct nuclear compartments using protein tethering, promiscuous biotinylation and quantitative proteomics. We will determine how DNA repair is orchestrated at different heterochromatin structures using a CRISPR/Cas9-based system that allows, for the first time robust induction of DSBs at specific heterochromatin compartments. Finally, we will investigate the role of 3D-genome folding in the kinetics of DNA repair and pathway choice using single nucleotide resolution DSB-mapping coupled to 3D-topological maps.
This proposal has significant implications for understanding the mechanisms controlling DNA repair within the nuclear environment and will reveal the regions of the genome that are susceptible to genomic instability and help us understand why certain mutations and translocations are recurrent in cancer
Max ERC Funding
1 999 750 €
Duration
Start date: 2017-03-01, End date: 2022-02-28
Project acronym 3DPBio
Project Computational Models of Motion for Fabrication-aware Design of Bioinspired Systems
Researcher (PI) Stelian Coros
Host Institution (HI) EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH
Country Switzerland
Call Details Consolidator Grant (CoG), PE6, ERC-2019-COG
Summary "Bridging the fields of Computer Animation and Computational Fabrication, this proposal will establish the foundations for algorithmic design of physical structures that can generate lifelike movements. Driven by embedded actuators, these types of structures will enable an abundance of possibilities for a wide array of real-world technologies: animatronic characters whose organic motions will enhance their ability to awe, entertain and educate; soft robotic creatures that are both skilled and safe to be around; patient-specific prosthetics and wearable devices that match the soft touch of the human body, etc. Recent advances in additive manufacturing (AM) technologies are particularly exciting in this context, as they allow us to create designs of unparalleled geometric complexity using a constantly expanding range of materials. And if past developments are an indication, within the next decade we will be able to fabricate physical structures that approach, at least at the macro scale, the functional sophistication of their biological counterparts. However, while this unprecedented capability enables fascinating opportunities, it also leads to an explosion in the dimensionality of the space that must be explored during the design process. As AM technologies keep evolving, the gap between ""what we can produce"" and ""what we can design"" is therefore rapidly growing.
To effectively leverage the extraordinary design possibilities enabled by AM, 3DPBio will develop the computational and mathematical foundations required to study a fundamental scientific question: how are physical deformations, mechanical movements and overall functional capabilities governed by geometric shape features, material compositions and the design of compliant actuation systems? By enabling computers to reason about this question, our work will establish new ways to algorithmically create digital designs that can be turned into mechanical lifeforms at the push of a button."
Summary
"Bridging the fields of Computer Animation and Computational Fabrication, this proposal will establish the foundations for algorithmic design of physical structures that can generate lifelike movements. Driven by embedded actuators, these types of structures will enable an abundance of possibilities for a wide array of real-world technologies: animatronic characters whose organic motions will enhance their ability to awe, entertain and educate; soft robotic creatures that are both skilled and safe to be around; patient-specific prosthetics and wearable devices that match the soft touch of the human body, etc. Recent advances in additive manufacturing (AM) technologies are particularly exciting in this context, as they allow us to create designs of unparalleled geometric complexity using a constantly expanding range of materials. And if past developments are an indication, within the next decade we will be able to fabricate physical structures that approach, at least at the macro scale, the functional sophistication of their biological counterparts. However, while this unprecedented capability enables fascinating opportunities, it also leads to an explosion in the dimensionality of the space that must be explored during the design process. As AM technologies keep evolving, the gap between ""what we can produce"" and ""what we can design"" is therefore rapidly growing.
To effectively leverage the extraordinary design possibilities enabled by AM, 3DPBio will develop the computational and mathematical foundations required to study a fundamental scientific question: how are physical deformations, mechanical movements and overall functional capabilities governed by geometric shape features, material compositions and the design of compliant actuation systems? By enabling computers to reason about this question, our work will establish new ways to algorithmically create digital designs that can be turned into mechanical lifeforms at the push of a button."
Max ERC Funding
2 000 000 €
Duration
Start date: 2020-02-01, End date: 2025-01-31
Project acronym 3DSPIN
Project 3-Dimensional Maps of the Spinning Nucleon
Researcher (PI) Alessandro Bacchetta
Host Institution (HI) UNIVERSITA DEGLI STUDI DI PAVIA
Country Italy
Call Details Consolidator Grant (CoG), PE2, ERC-2014-CoG
Summary How does the inside of the proton look like? What generates its spin?
3DSPIN will deliver essential information to answer these questions at the frontier of subnuclear physics.
At present, we have detailed maps of the distribution of quarks and gluons in the nucleon in 1D (as a function of their momentum in a single direction). We also know that quark spins account for only about 1/3 of the spin of the nucleon.
3DSPIN will lead the way into a new stage of nucleon mapping, explore the distribution of quarks in full 3D momentum space and obtain unprecedented information on orbital angular momentum.
Goals
1. extract from experimental data the 3D distribution of quarks (in momentum space), as described by Transverse-Momentum Distributions (TMDs);
2. obtain from TMDs information on quark Orbital Angular Momentum (OAM).
Methodology
3DSPIN will implement state-of-the-art fitting procedures to analyze relevant experimental data and extract quark TMDs, similarly to global fits of standard parton distribution functions. Information about quark angular momentum will be obtained through assumptions based on theoretical considerations. The next five years represent an ideal time window to accomplish our goals, thanks to the wealth of expected data from deep-inelastic scattering experiments (COMPASS, Jefferson Lab), hadronic colliders (Fermilab, BNL, LHC), and electron-positron colliders (BELLE, BABAR). The PI has a strong reputation in this field. The group will operate in partnership with the Italian National Institute of Nuclear Physics and in close interaction with leading experts and experimental collaborations worldwide.
Impact
Mapping the 3D structure of chemical compounds has revolutionized chemistry. Similarly, mapping the 3D structure of the nucleon will have a deep impact on our understanding of the fundamental constituents of matter. We will open new perspectives on the dynamics of quarks and gluons and sharpen our view of high-energy processes involving nucleons.
Summary
How does the inside of the proton look like? What generates its spin?
3DSPIN will deliver essential information to answer these questions at the frontier of subnuclear physics.
At present, we have detailed maps of the distribution of quarks and gluons in the nucleon in 1D (as a function of their momentum in a single direction). We also know that quark spins account for only about 1/3 of the spin of the nucleon.
3DSPIN will lead the way into a new stage of nucleon mapping, explore the distribution of quarks in full 3D momentum space and obtain unprecedented information on orbital angular momentum.
Goals
1. extract from experimental data the 3D distribution of quarks (in momentum space), as described by Transverse-Momentum Distributions (TMDs);
2. obtain from TMDs information on quark Orbital Angular Momentum (OAM).
Methodology
3DSPIN will implement state-of-the-art fitting procedures to analyze relevant experimental data and extract quark TMDs, similarly to global fits of standard parton distribution functions. Information about quark angular momentum will be obtained through assumptions based on theoretical considerations. The next five years represent an ideal time window to accomplish our goals, thanks to the wealth of expected data from deep-inelastic scattering experiments (COMPASS, Jefferson Lab), hadronic colliders (Fermilab, BNL, LHC), and electron-positron colliders (BELLE, BABAR). The PI has a strong reputation in this field. The group will operate in partnership with the Italian National Institute of Nuclear Physics and in close interaction with leading experts and experimental collaborations worldwide.
Impact
Mapping the 3D structure of chemical compounds has revolutionized chemistry. Similarly, mapping the 3D structure of the nucleon will have a deep impact on our understanding of the fundamental constituents of matter. We will open new perspectives on the dynamics of quarks and gluons and sharpen our view of high-energy processes involving nucleons.
Max ERC Funding
1 509 000 €
Duration
Start date: 2015-07-01, End date: 2020-12-31
Project acronym 3MC
Project 3D Model Catalysts to explore new routes to sustainable fuels
Researcher (PI) Petra Elisabeth De jongh
Host Institution (HI) UNIVERSITEIT UTRECHT
Country Netherlands
Call Details Consolidator Grant (CoG), PE4, ERC-2014-CoG
Summary Currently fuels, plastics, and drugs are predominantly manufactured from oil. A transition towards renewable resources critically depends on new catalysts, for instance to convert small molecules (such as solar or biomass derived hydrogen, carbon monoxide, water and carbon dioxide) into more complex ones (such as oxygenates, containing oxygen atoms in their structure). Catalyst development now often depends on trial and error rather than rational design, as the heterogeneity of these composite systems hampers detailed understanding of the role of each of the components.
I propose 3D model catalysts as a novel enabling tool to overcome this problem. Their well-defined nature allows unprecedented precision in the variation of structural parameters (morphology, spatial distribution) of the individual components, while at the same time they mimic real catalysts closely enough to allow testing under industrially relevant conditions. Using this approach I will address fundamental questions, such as:
* What are the mechanisms (structural, electronic, chemical) by which non-metal promoters influence the functionality of copper-based catalysts?
* Which nanoalloys can be formed, how does their composition influence the surface active sites and catalytic functionality under reaction conditions?
* Which size and interface effects occur, and how can we use them to tune the actitivity and selectivity towards desired products?
Our 3D model catalysts will be assembled from ordered mesoporous silica and carbon support materials and Cu-based promoted and bimetallic nanoparticles. The combination with high resolution characterization and testing under realistic conditions allows detailed insight into the role of the different components; critical for the rational design of novel catalysts for a future more sustainable production of chemicals and fuels from renewable resources.
Summary
Currently fuels, plastics, and drugs are predominantly manufactured from oil. A transition towards renewable resources critically depends on new catalysts, for instance to convert small molecules (such as solar or biomass derived hydrogen, carbon monoxide, water and carbon dioxide) into more complex ones (such as oxygenates, containing oxygen atoms in their structure). Catalyst development now often depends on trial and error rather than rational design, as the heterogeneity of these composite systems hampers detailed understanding of the role of each of the components.
I propose 3D model catalysts as a novel enabling tool to overcome this problem. Their well-defined nature allows unprecedented precision in the variation of structural parameters (morphology, spatial distribution) of the individual components, while at the same time they mimic real catalysts closely enough to allow testing under industrially relevant conditions. Using this approach I will address fundamental questions, such as:
* What are the mechanisms (structural, electronic, chemical) by which non-metal promoters influence the functionality of copper-based catalysts?
* Which nanoalloys can be formed, how does their composition influence the surface active sites and catalytic functionality under reaction conditions?
* Which size and interface effects occur, and how can we use them to tune the actitivity and selectivity towards desired products?
Our 3D model catalysts will be assembled from ordered mesoporous silica and carbon support materials and Cu-based promoted and bimetallic nanoparticles. The combination with high resolution characterization and testing under realistic conditions allows detailed insight into the role of the different components; critical for the rational design of novel catalysts for a future more sustainable production of chemicals and fuels from renewable resources.
Max ERC Funding
1 999 625 €
Duration
Start date: 2015-09-01, End date: 2020-11-30
Project acronym 4DPHOTON
Project Beyond Light Imaging: High-Rate Single-Photon Detection in Four Dimensions
Researcher (PI) Massimiliano FIORINI
Host Institution (HI) ISTITUTO NAZIONALE DI FISICA NUCLEARE
Country Italy
Call Details Consolidator Grant (CoG), PE2, ERC-2018-COG
Summary Goal of the 4DPHOTON project is the development and construction of a photon imaging detector with unprecedented performance. The proposed device will be capable of detecting fluxes of single-photons up to one billion photons per second, over areas of several square centimetres, and will measure - for each photon - position and time simultaneously with resolutions better than ten microns and few tens of picoseconds, respectively. These figures of merit will open many important applications allowing significant advances in particle physics, life sciences or other emerging fields where excellent timing and position resolutions are simultaneously required.
Our goal will be achieved thanks to the use of an application-specific integrated circuit in 65 nm complementary metal-oxide-semiconductor (CMOS) technology, that will deliver a timing resolution of few tens of picoseconds at the pixel level, over few hundred thousand individually-active pixel channels, allowing very high rates of photons to be detected, and the corresponding information digitized and transferred to a processing unit.
As a result of the 4DPHOTON project we will remove the constraints that many light imaging applications have due to the lack of precise single-photon information on four dimensions (4D): the three spatial coordinates and time simultaneously. In particular, we will prove the performance of this detector in the field of particle physics, performing the reconstruction of Cherenkov photon rings with a timing resolution of ten picoseconds. With its excellent granularity, timing resolution, rate capability and compactness, this detector will represent a new paradigm for the realisation of future Ring Imaging Cherenkov detectors, capable of achieving high efficiency particle identification in environments with very high particle multiplicities, exploiting time-association of the photon hits.
Summary
Goal of the 4DPHOTON project is the development and construction of a photon imaging detector with unprecedented performance. The proposed device will be capable of detecting fluxes of single-photons up to one billion photons per second, over areas of several square centimetres, and will measure - for each photon - position and time simultaneously with resolutions better than ten microns and few tens of picoseconds, respectively. These figures of merit will open many important applications allowing significant advances in particle physics, life sciences or other emerging fields where excellent timing and position resolutions are simultaneously required.
Our goal will be achieved thanks to the use of an application-specific integrated circuit in 65 nm complementary metal-oxide-semiconductor (CMOS) technology, that will deliver a timing resolution of few tens of picoseconds at the pixel level, over few hundred thousand individually-active pixel channels, allowing very high rates of photons to be detected, and the corresponding information digitized and transferred to a processing unit.
As a result of the 4DPHOTON project we will remove the constraints that many light imaging applications have due to the lack of precise single-photon information on four dimensions (4D): the three spatial coordinates and time simultaneously. In particular, we will prove the performance of this detector in the field of particle physics, performing the reconstruction of Cherenkov photon rings with a timing resolution of ten picoseconds. With its excellent granularity, timing resolution, rate capability and compactness, this detector will represent a new paradigm for the realisation of future Ring Imaging Cherenkov detectors, capable of achieving high efficiency particle identification in environments with very high particle multiplicities, exploiting time-association of the photon hits.
Max ERC Funding
1 975 000 €
Duration
Start date: 2019-12-01, End date: 2024-11-30
Project acronym 4DRepLy
Project Closing the 4D Real World Reconstruction Loop
Researcher (PI) Christian THEOBALT
Host Institution (HI) MAX-PLANCK-GESELLSCHAFT ZUR FORDERUNG DER WISSENSCHAFTEN EV
Country Germany
Call Details Consolidator Grant (CoG), PE6, ERC-2017-COG
Summary 4D reconstruction, the camera-based dense dynamic scene reconstruction, is a grand challenge in computer graphics and computer vision. Despite great progress, 4D capturing the complex, diverse real world outside a studio is still far from feasible. 4DRepLy builds a new generation of high-fidelity 4D reconstruction (4DRecon) methods. They will be the first to efficiently capture all types of deformable objects (humans and other types) in crowded real world scenes with a single color or depth camera. They capture space-time coherent deforming geometry, motion, high-frequency reflectance and illumination at unprecedented detail, and will be the first to handle difficult occlusions, topology changes and large groups of interacting objects. They automatically adapt to new scene types, yet deliver models with meaningful, interpretable parameters. This requires far reaching contributions: First, we develop groundbreaking new plasticity-enhanced model-based 4D reconstruction methods that automatically adapt to new scenes. Second, we develop radically new machine learning-based dense 4D reconstruction methods. Third, these model- and learning-based methods are combined in two revolutionary new classes of 4DRecon methods: 1) advanced fusion-based methods and 2) methods with deep architectural integration. Both, 1) and 2), are automatically designed in the 4D Real World Reconstruction Loop, a revolutionary new design paradigm in which 4DRecon methods refine and adapt themselves while continuously processing unlabeled real world input. This overcomes the previously unbreakable scalability barrier to real world scene diversity, complexity and generality. This paradigm shift opens up a new research direction in graphics and vision and has far reaching relevance across many scientific fields. It enables new applications of profound social pervasion and significant economic impact, e.g., for visual media and virtual/augmented reality, and for future autonomous and robotic systems.
Summary
4D reconstruction, the camera-based dense dynamic scene reconstruction, is a grand challenge in computer graphics and computer vision. Despite great progress, 4D capturing the complex, diverse real world outside a studio is still far from feasible. 4DRepLy builds a new generation of high-fidelity 4D reconstruction (4DRecon) methods. They will be the first to efficiently capture all types of deformable objects (humans and other types) in crowded real world scenes with a single color or depth camera. They capture space-time coherent deforming geometry, motion, high-frequency reflectance and illumination at unprecedented detail, and will be the first to handle difficult occlusions, topology changes and large groups of interacting objects. They automatically adapt to new scene types, yet deliver models with meaningful, interpretable parameters. This requires far reaching contributions: First, we develop groundbreaking new plasticity-enhanced model-based 4D reconstruction methods that automatically adapt to new scenes. Second, we develop radically new machine learning-based dense 4D reconstruction methods. Third, these model- and learning-based methods are combined in two revolutionary new classes of 4DRecon methods: 1) advanced fusion-based methods and 2) methods with deep architectural integration. Both, 1) and 2), are automatically designed in the 4D Real World Reconstruction Loop, a revolutionary new design paradigm in which 4DRecon methods refine and adapt themselves while continuously processing unlabeled real world input. This overcomes the previously unbreakable scalability barrier to real world scene diversity, complexity and generality. This paradigm shift opens up a new research direction in graphics and vision and has far reaching relevance across many scientific fields. It enables new applications of profound social pervasion and significant economic impact, e.g., for visual media and virtual/augmented reality, and for future autonomous and robotic systems.
Max ERC Funding
1 977 000 €
Duration
Start date: 2018-09-01, End date: 2023-08-31
Project acronym A-FRO
Project Actively Frozen - contextual modulation of freezing and its neuronal basis
Researcher (PI) Marta de Aragao Pacheco Moita
Host Institution (HI) FUNDACAO D. ANNA SOMMER CHAMPALIMAUD E DR. CARLOS MONTEZ CHAMPALIMAUD
Country Portugal
Call Details Consolidator Grant (CoG), LS5, ERC-2018-COG
Summary When faced with a threat, an animal must decide whether to freeze, reducing its chances of being noticed, or to flee to the safety of a refuge. Animals from fish to primates choose between these two alternatives when confronted by an attacking predator, a choice that largely depends on the context in which the threat occurs. Recent work has made strides identifying the pre-motor circuits, and their inputs, which control freezing behavior in rodents, but how contextual information is integrated to guide this choice is still far from understood. We recently found that fruit flies in response to visual looming stimuli, simulating a large object on collision course, make rapid freeze/flee choices that depend on the social and spatial environment, and the fly’s internal state. Further, identification of looming detector neurons was recently reported and we identified the descending command neurons, DNp09, responsible for freezing in the fly. Knowing the sensory input and descending output for looming-evoked freezing, two environmental factors that modulate its expression, and using a genetically tractable system affording the use of large sample sizes, places us in an unique position to understand how a information about a threat is integrated with cues from the environment to guide the choice of whether to freeze (our goal). To assess how social information impinges on the circuit for freezing, we will examine the sensory inputs and neuromodulators that mediate this process, mapping their connections to DNp09 neurons (Aim 1). We ask whether learning is required for the spatial modulation of freezing, which cues flies are using to discriminate different places and which brain circuits mediate this process (Aim 2). Finally, we will study how activity of DNp09 neurons drives freezing (Aim 3). This project will provide a comprehensive understanding of the mechanism of freezing and its modulation by the environment, from single neurons to behaviour.
Summary
When faced with a threat, an animal must decide whether to freeze, reducing its chances of being noticed, or to flee to the safety of a refuge. Animals from fish to primates choose between these two alternatives when confronted by an attacking predator, a choice that largely depends on the context in which the threat occurs. Recent work has made strides identifying the pre-motor circuits, and their inputs, which control freezing behavior in rodents, but how contextual information is integrated to guide this choice is still far from understood. We recently found that fruit flies in response to visual looming stimuli, simulating a large object on collision course, make rapid freeze/flee choices that depend on the social and spatial environment, and the fly’s internal state. Further, identification of looming detector neurons was recently reported and we identified the descending command neurons, DNp09, responsible for freezing in the fly. Knowing the sensory input and descending output for looming-evoked freezing, two environmental factors that modulate its expression, and using a genetically tractable system affording the use of large sample sizes, places us in an unique position to understand how a information about a threat is integrated with cues from the environment to guide the choice of whether to freeze (our goal). To assess how social information impinges on the circuit for freezing, we will examine the sensory inputs and neuromodulators that mediate this process, mapping their connections to DNp09 neurons (Aim 1). We ask whether learning is required for the spatial modulation of freezing, which cues flies are using to discriminate different places and which brain circuits mediate this process (Aim 2). Finally, we will study how activity of DNp09 neurons drives freezing (Aim 3). This project will provide a comprehensive understanding of the mechanism of freezing and its modulation by the environment, from single neurons to behaviour.
Max ERC Funding
1 969 750 €
Duration
Start date: 2019-02-01, End date: 2024-01-31
Project acronym ABIONYS
Project Artificial Enzyme Modules as Tools in a Tailor-made Biosynthesis
Researcher (PI) Jan DESKA
Host Institution (HI) AALTO KORKEAKOULUSAATIO SR
Country Finland
Call Details Consolidator Grant (CoG), PE5, ERC-2019-COG
Summary In order to tackle some of the prime societal challenges of this century, science has to urgently provide effective tools addressing the redesign of chemical value chains through the exploitation of novel, bio-based raw materials, and the discovery and implementation of more resource-efficient production platforms. Nature will inevitably play a pivotal role in the imminent transformation of industrial strategies, and the recent bioeconomy approaches can only be regarded as initial step towards a sustainable future. Operating at the interface between chemistry and life sciences, my ABIONYS will fundamentally challenge the widely held distinction separating chemical from biosynthesis, and will deliver the first proof-of-concept where abiotic reactions act as productive puzzle pieces in biosynthetic arrangements. On the basis of our previous ground-breaking discoveries on artificial enzyme functions, I will create a significantly extended toolbox of biocatalysis modules by applying protein-based interpretations of synthetically crucial but non-natural reactions i.e. transformations that are in no way biosynthetically encoded in living organisms. My research will exploit these tools in multi-enzyme cascades for the preparation of complex organic target structures, not only to highlight the great synthetic potential of these approaches, but also to lay the groundwork for in vivo implementations. Eventually, the knowledge gathered from enzyme discovery and cascade design will enable to create an unprecedented class of bioproduction systems, where the genetic incorporation of artificial enzyme functions into recombinant microbial host organisms will yield tailor-made cellular factories. Combining classical organic synthesis strategies with the power of modern biotechnology, ABIONYS is going to transform the way we synthesize complex and functional building blocks by allowing us to encode organic chemistry thinking into living production platforms.
Summary
In order to tackle some of the prime societal challenges of this century, science has to urgently provide effective tools addressing the redesign of chemical value chains through the exploitation of novel, bio-based raw materials, and the discovery and implementation of more resource-efficient production platforms. Nature will inevitably play a pivotal role in the imminent transformation of industrial strategies, and the recent bioeconomy approaches can only be regarded as initial step towards a sustainable future. Operating at the interface between chemistry and life sciences, my ABIONYS will fundamentally challenge the widely held distinction separating chemical from biosynthesis, and will deliver the first proof-of-concept where abiotic reactions act as productive puzzle pieces in biosynthetic arrangements. On the basis of our previous ground-breaking discoveries on artificial enzyme functions, I will create a significantly extended toolbox of biocatalysis modules by applying protein-based interpretations of synthetically crucial but non-natural reactions i.e. transformations that are in no way biosynthetically encoded in living organisms. My research will exploit these tools in multi-enzyme cascades for the preparation of complex organic target structures, not only to highlight the great synthetic potential of these approaches, but also to lay the groundwork for in vivo implementations. Eventually, the knowledge gathered from enzyme discovery and cascade design will enable to create an unprecedented class of bioproduction systems, where the genetic incorporation of artificial enzyme functions into recombinant microbial host organisms will yield tailor-made cellular factories. Combining classical organic synthesis strategies with the power of modern biotechnology, ABIONYS is going to transform the way we synthesize complex and functional building blocks by allowing us to encode organic chemistry thinking into living production platforms.
Max ERC Funding
1 995 707 €
Duration
Start date: 2020-11-01, End date: 2025-10-31