Project acronym BIRTH
Project Births, mothers and babies: prehistoric fertility in the Balkans between 10000 – 5000 BC
Researcher (PI) Sofija Stefanovic
Host Institution (HI) BIOSENSE INSTITUTE - RESEARCH AND DEVELOPMENT INSTITUTE FOR INFORMATION TECHNOLOGIES IN BIOSYSTEMS
Call Details Starting Grant (StG), SH6, ERC-2014-STG
Summary The BIRTH project will investigate the key biological and cultural mechanisms affecting fertility rates resulting the Neolithic Demogaphic Transition, the major demographic shift in human evolution. We integrate skeletal markers with micro-nutritional and macro-scaled cultural effects on fertility rates during the Early-Middle Holocene (10000-5000 BC) in the Central Balkans. Human, animal and plant remains, will be analysed using methods from bioarchaeological, forensic, chemical sciences in order to: 1) Investigate variability in the pattern of birth rates (number of pregnancies, interval(s) between them and the duration of the reproductive period) through histological analysis of irregularities in tooth cementum of women; 2) Determine paleoobstetric and neonatal body characteristics, health status and nutrition through analysis of skeletal remains; 3) Determine micronutritional changes during the Early-Middle Holocene through trace element (Zn, Ca and Fe) analysis; 4) Investigate the micro and macronutritional value of prehistoric foodstuffs, through an analysis of animal and plant remains and to compare the nutritional intake in relation to health and fertility; 5) Establish a chronology of the NDT in the Balkans by summed radiocarbon probability distributions; 6) Explore the possible role of culture in driving fertility increases, through analysis of community attitudes to birthing trough investigation of neonate graves and artifact connected to the birthing process. Given that the issues of health and fertility are of utmost importance in the present as they were in the past, the BIRTH project offers new understanding of biocultural mechanisms which led to fertility increase and novel approaches to ancient skeletal heritage, and emphasizes their great potential for modern humanity.
Summary
The BIRTH project will investigate the key biological and cultural mechanisms affecting fertility rates resulting the Neolithic Demogaphic Transition, the major demographic shift in human evolution. We integrate skeletal markers with micro-nutritional and macro-scaled cultural effects on fertility rates during the Early-Middle Holocene (10000-5000 BC) in the Central Balkans. Human, animal and plant remains, will be analysed using methods from bioarchaeological, forensic, chemical sciences in order to: 1) Investigate variability in the pattern of birth rates (number of pregnancies, interval(s) between them and the duration of the reproductive period) through histological analysis of irregularities in tooth cementum of women; 2) Determine paleoobstetric and neonatal body characteristics, health status and nutrition through analysis of skeletal remains; 3) Determine micronutritional changes during the Early-Middle Holocene through trace element (Zn, Ca and Fe) analysis; 4) Investigate the micro and macronutritional value of prehistoric foodstuffs, through an analysis of animal and plant remains and to compare the nutritional intake in relation to health and fertility; 5) Establish a chronology of the NDT in the Balkans by summed radiocarbon probability distributions; 6) Explore the possible role of culture in driving fertility increases, through analysis of community attitudes to birthing trough investigation of neonate graves and artifact connected to the birthing process. Given that the issues of health and fertility are of utmost importance in the present as they were in the past, the BIRTH project offers new understanding of biocultural mechanisms which led to fertility increase and novel approaches to ancient skeletal heritage, and emphasizes their great potential for modern humanity.
Max ERC Funding
1 714 880 €
Duration
Start date: 2015-10-01, End date: 2020-09-30
Project acronym EvoConBiO
Project Uncovering and engineering the principles governing evolution and cellular control of bioenergetic organelles
Researcher (PI) Iain JOHNSTON
Host Institution (HI) UNIVERSITETET I BERGEN
Call Details Starting Grant (StG), LS8, ERC-2018-STG
Summary "Complex life on Earth is powered by bioenergetic organelles -- mitochondria and chloroplasts. Originally independent organisms, these organelles have retained their own genomes (mtDNA and cpDNA), which have been dramatically reduced through evolutionary history. Organelle genomes form dynamic populations within present-day eukaryotic cells, akin to individuals co-evolving in a ""cellular ecosystem"". The structure of these populations is central to eukaryotic life. However, the processes shaping the content of these genomes through history, and maintaining their integrity in modern organisms, are poorly understood. This challenges our understanding of eukaryotic evolution and our ability to design rational strategies to engineer bioenergetic performance.
EvoConBiO will address these questions using a unique and unprecedented interdisciplinary approach, combining experimental characterisation and manipulation of organelle genomes with mathematical modelling and cutting-edge statistics. This highly novel combination of experiment and theory will drive the field in a new direction, for the first time uncovering the universal principles underlying the evolution and cellular control of mitochondria and chloroplasts. Our groundbreaking recent work on mtDNA suggests a common tension underlying organelle evolution, between genetic robustness (transferring genes to the nucleus) and the control and maintenance of organelles (retaining genes in organelles). EvoConBiO will reveal the pathways underlying organelle evolution, why organisms adapt to different points on these pathways, and how they resolve this underlying tension. In addition to these ""blue sky"" scientific insights into a process of central evolutionary importance, we will harness our findings to ""learn from evolution"" in high-risk high-reward development of new experimental strategies to engineer chloroplast performance in plants and algae of importance in EU agriculture, biofuel production, and bioengineering."
Summary
"Complex life on Earth is powered by bioenergetic organelles -- mitochondria and chloroplasts. Originally independent organisms, these organelles have retained their own genomes (mtDNA and cpDNA), which have been dramatically reduced through evolutionary history. Organelle genomes form dynamic populations within present-day eukaryotic cells, akin to individuals co-evolving in a ""cellular ecosystem"". The structure of these populations is central to eukaryotic life. However, the processes shaping the content of these genomes through history, and maintaining their integrity in modern organisms, are poorly understood. This challenges our understanding of eukaryotic evolution and our ability to design rational strategies to engineer bioenergetic performance.
EvoConBiO will address these questions using a unique and unprecedented interdisciplinary approach, combining experimental characterisation and manipulation of organelle genomes with mathematical modelling and cutting-edge statistics. This highly novel combination of experiment and theory will drive the field in a new direction, for the first time uncovering the universal principles underlying the evolution and cellular control of mitochondria and chloroplasts. Our groundbreaking recent work on mtDNA suggests a common tension underlying organelle evolution, between genetic robustness (transferring genes to the nucleus) and the control and maintenance of organelles (retaining genes in organelles). EvoConBiO will reveal the pathways underlying organelle evolution, why organisms adapt to different points on these pathways, and how they resolve this underlying tension. In addition to these ""blue sky"" scientific insights into a process of central evolutionary importance, we will harness our findings to ""learn from evolution"" in high-risk high-reward development of new experimental strategies to engineer chloroplast performance in plants and algae of importance in EU agriculture, biofuel production, and bioengineering."
Max ERC Funding
1 417 862 €
Duration
Start date: 2019-07-01, End date: 2024-06-30
Project acronym NCGQG
Project Noncommutative geometry and quantum groups
Researcher (PI) Sergiy Neshveyev
Host Institution (HI) UNIVERSITETET I OSLO
Call Details Starting Grant (StG), PE1, ERC-2012-StG_20111012
Summary "The goal of the project is to make fundamental contributions to the study of quantum groups in the operator algebraic setting. Two main directions it aims to explore are noncommutative differential geometry and boundary theory of quantum random walks.
The idea behind noncommutative geometry is to bring geometric insight to the study of noncommutative algebras and to analyze spaces which are beyond the reach via classical means. It has been particularly successful in the latter, for example, in the study of the spaces of leaves of foliations. Quantum groups supply plenty of examples of noncommutative algebras, but the question how they fit into noncommutative geometry remains complicated. A successful union of these two areas is important for testing ideas of noncommutative geometry and for its development in new directions. One of the main goals of the project is to use the momentum created by our recent work in the area in order to further expand the boundaries of our understanding. Specifically, we are going to study such problems as the local index formula, equivariance of Dirac operators with respect to the dual group action (with an eye towards the Baum-Connes conjecture for discrete quantum groups), construction of Dirac operators on quantum homogeneous spaces, structure of quantized C*-algebras of continuous functions, computation of dual cohomology of compact quantum groups.
The boundary theory of quantum random walks was created around ten years ago. In the recent years there has been a lot of progress on the “measure-theoretic” side of the theory, while the questions largely remain open on the “topological” side. A significant progress in this area can have a great influence on understanding of quantum groups, construction of new examples and development of quantum probability. The main problems we are going to study are boundary convergence of quantum random walks and computation of Martin boundaries."
Summary
"The goal of the project is to make fundamental contributions to the study of quantum groups in the operator algebraic setting. Two main directions it aims to explore are noncommutative differential geometry and boundary theory of quantum random walks.
The idea behind noncommutative geometry is to bring geometric insight to the study of noncommutative algebras and to analyze spaces which are beyond the reach via classical means. It has been particularly successful in the latter, for example, in the study of the spaces of leaves of foliations. Quantum groups supply plenty of examples of noncommutative algebras, but the question how they fit into noncommutative geometry remains complicated. A successful union of these two areas is important for testing ideas of noncommutative geometry and for its development in new directions. One of the main goals of the project is to use the momentum created by our recent work in the area in order to further expand the boundaries of our understanding. Specifically, we are going to study such problems as the local index formula, equivariance of Dirac operators with respect to the dual group action (with an eye towards the Baum-Connes conjecture for discrete quantum groups), construction of Dirac operators on quantum homogeneous spaces, structure of quantized C*-algebras of continuous functions, computation of dual cohomology of compact quantum groups.
The boundary theory of quantum random walks was created around ten years ago. In the recent years there has been a lot of progress on the “measure-theoretic” side of the theory, while the questions largely remain open on the “topological” side. A significant progress in this area can have a great influence on understanding of quantum groups, construction of new examples and development of quantum probability. The main problems we are going to study are boundary convergence of quantum random walks and computation of Martin boundaries."
Max ERC Funding
1 144 930 €
Duration
Start date: 2013-01-01, End date: 2017-12-31
Project acronym PaPaAlg
Project Pareto-Optimal Parameterized Algorithms
Researcher (PI) Daniel LOKSHTANOV
Host Institution (HI) UNIVERSITETET I BERGEN
Call Details Starting Grant (StG), PE6, ERC-2016-STG
Summary In this project we revise the foundations of parameterized complexity, a modern multi-variate approach to algorithm design. The underlying question of every algorithmic paradigm is ``what is the best algorithm?'' When the running time of algorithms is measured in terms of only one variable, it is easy to compare which one is the fastest. However, when the running time depends on more than one variable, as is the case for parameterized complexity:
**It is not clear what a ``fastest possible algorithm'' really means.**
The previous formalizations of what a fastest possible parameterized algorithm means are one-dimensional, contrary to the core philosophy of parameterized complexity. These one-dimensional approaches to a multi-dimensional algorithmic paradigm unavoidably miss the most efficient algorithms, and ultimately fail to solve instances that we could have solved.
We propose the first truly multi-dimensional framework for comparing the running times of parameterized algorithms. Our new definitions are based on the notion of Pareto-optimality from economics. The new approach encompasses all existing paradigms for comparing parameterized algorithms, opens up a whole new world of research directions in parameterized complexity, and reveals new fundamental questions about parameterized problems that were considered well-understood.
In this project we will develop powerful algorithmic and complexity theoretic tools to answer these research questions. The successful completion of this project will take parameterized complexity far beyond the state of the art, make parameterized algorithms more relevant for practical applications, and significantly advance adjacent subfields of theoretical computer science and mathematics.
Summary
In this project we revise the foundations of parameterized complexity, a modern multi-variate approach to algorithm design. The underlying question of every algorithmic paradigm is ``what is the best algorithm?'' When the running time of algorithms is measured in terms of only one variable, it is easy to compare which one is the fastest. However, when the running time depends on more than one variable, as is the case for parameterized complexity:
**It is not clear what a ``fastest possible algorithm'' really means.**
The previous formalizations of what a fastest possible parameterized algorithm means are one-dimensional, contrary to the core philosophy of parameterized complexity. These one-dimensional approaches to a multi-dimensional algorithmic paradigm unavoidably miss the most efficient algorithms, and ultimately fail to solve instances that we could have solved.
We propose the first truly multi-dimensional framework for comparing the running times of parameterized algorithms. Our new definitions are based on the notion of Pareto-optimality from economics. The new approach encompasses all existing paradigms for comparing parameterized algorithms, opens up a whole new world of research directions in parameterized complexity, and reveals new fundamental questions about parameterized problems that were considered well-understood.
In this project we will develop powerful algorithmic and complexity theoretic tools to answer these research questions. The successful completion of this project will take parameterized complexity far beyond the state of the art, make parameterized algorithms more relevant for practical applications, and significantly advance adjacent subfields of theoretical computer science and mathematics.
Max ERC Funding
1 499 557 €
Duration
Start date: 2017-02-01, End date: 2022-01-31
Project acronym PARAPPROX
Project Parameterized Approximation
Researcher (PI) Saket Saurabh
Host Institution (HI) UNIVERSITETET I BERGEN
Call Details Starting Grant (StG), PE6, ERC-2012-StG_20111012
Summary "The main goal of this project is to lay the foundations of a ``non-polynomial time theory of approximation"" -- the Parameterized Approximation for NP-hard optimization problems. A combination that will use the salient features of Approximation Algorithms and
Parameterized Complexity. In the former, one relaxes the requirement of finding an optimum solution. In the latter, one relaxes the requirement of finishing in polynomial time by restricting the
combinatorial explosion in the running time to a parameter that for reasonable inputs is much smaller than the input size. This project will explore the following fundamental question:
Approximation Algorithms + Parameterized Complexity=?
New techniques will be developed that will simultaneously utilize the notions of relaxed time complexity and accuracy and thereby make problems for which both these approaches have failed independently, tractable. It is however conceivable that for some problems even this combined approach may not succeed. But in those situations we will glean valuable insight into the reasons for failure. In parallel to algorithmic studies, an intractability theory will be
developed which will provide the theoretical framework to specify the extent to which this approach might work. Thus, on one hand the project will give rise to algorithms that will have impact beyond the boundaries of computer science and on the other hand it will lead to a complexity theory that will go beyond the established notions of intractability. Both these aspects of my project are groundbreaking -- the new theory will transcend our current ideas of
efficient approximation and thereby raise the state of the art to a new level."
Summary
"The main goal of this project is to lay the foundations of a ``non-polynomial time theory of approximation"" -- the Parameterized Approximation for NP-hard optimization problems. A combination that will use the salient features of Approximation Algorithms and
Parameterized Complexity. In the former, one relaxes the requirement of finding an optimum solution. In the latter, one relaxes the requirement of finishing in polynomial time by restricting the
combinatorial explosion in the running time to a parameter that for reasonable inputs is much smaller than the input size. This project will explore the following fundamental question:
Approximation Algorithms + Parameterized Complexity=?
New techniques will be developed that will simultaneously utilize the notions of relaxed time complexity and accuracy and thereby make problems for which both these approaches have failed independently, tractable. It is however conceivable that for some problems even this combined approach may not succeed. But in those situations we will glean valuable insight into the reasons for failure. In parallel to algorithmic studies, an intractability theory will be
developed which will provide the theoretical framework to specify the extent to which this approach might work. Thus, on one hand the project will give rise to algorithms that will have impact beyond the boundaries of computer science and on the other hand it will lead to a complexity theory that will go beyond the established notions of intractability. Both these aspects of my project are groundbreaking -- the new theory will transcend our current ideas of
efficient approximation and thereby raise the state of the art to a new level."
Max ERC Funding
1 690 000 €
Duration
Start date: 2013-01-01, End date: 2017-12-31
Project acronym STUCCOFIELDS
Project Structure and scaling in computational field theories
Researcher (PI) Snorre Harald Christiansen
Host Institution (HI) UNIVERSITETET I OSLO
Call Details Starting Grant (StG), PE1, ERC-2011-StG_20101014
Summary "The numerical simulations that are used in science and industry require ever more sophisticated mathematics. For the partial differential equations that are used to model physical processes, qualitative properties such as conserved quantities and monotonicity are crucial for well-posedness. Mimicking them in the discretizations seems equally important to get reliable results.
This project will contribute to the interplay of geometry and numerical analysis by bridging the gap between Lie group based techniques and finite elements. The role of Lie algebra valued differential forms will be highlighted. One aim is to develop construction techniques for complexes of finite element spaces incorporating special functions adapted to singular perturbations. Another is to marry finite elements with holonomy based discretizations used in mathematical physics, such as the Lattice Gauge Theory of particle physics and the Regge calculus of general relativity. Stability and convergence of algorithms will be related to differential geometric properties, and the interface between numerical analysis and quantum field theory will be explored. The techniques will be applied to the simulation of mechanics of complex materials and light-matter interactions."
Summary
"The numerical simulations that are used in science and industry require ever more sophisticated mathematics. For the partial differential equations that are used to model physical processes, qualitative properties such as conserved quantities and monotonicity are crucial for well-posedness. Mimicking them in the discretizations seems equally important to get reliable results.
This project will contribute to the interplay of geometry and numerical analysis by bridging the gap between Lie group based techniques and finite elements. The role of Lie algebra valued differential forms will be highlighted. One aim is to develop construction techniques for complexes of finite element spaces incorporating special functions adapted to singular perturbations. Another is to marry finite elements with holonomy based discretizations used in mathematical physics, such as the Lattice Gauge Theory of particle physics and the Regge calculus of general relativity. Stability and convergence of algorithms will be related to differential geometric properties, and the interface between numerical analysis and quantum field theory will be explored. The techniques will be applied to the simulation of mechanics of complex materials and light-matter interactions."
Max ERC Funding
1 100 000 €
Duration
Start date: 2012-01-01, End date: 2016-12-31
Project acronym Waterscales
Project Mathematical and computational foundations for modeling cerebral fluid flow.
Researcher (PI) Marie Elisabeth ROGNES
Host Institution (HI) SIMULA RESEARCH LABORATORY AS
Call Details Starting Grant (StG), PE1, ERC-2016-STG
Summary Your brain has its own waterscape: whether you are reading or sleeping, fluid flows through the brain tissue and clears waste in the process. These physiological processes are crucial for the well-being of the brain. In spite of their importance we understand them but little. Mathematics and numerics could play a crucial role in gaining new insight. Indeed, medical doctors express an urgent need for multiscale modeling of water transport through the brain, to overcome limitations in traditional techniques. Surprisingly little attention has been paid to the numerics of the brain's waterscape however, and fundamental knowledge is missing.
In response, the Waterscales ambition is to establish the mathematical and computational foundations for predictively modeling fluid flow and solute transport through the brain across scales -- from the cellular to the organ level. The project aims to bridge multiscale fluid mechanics and cellular electrophysiology to pioneer new families of mathematical models that couple macroscale, mesoscale and microscale flow with glial cell dynamics. For these models, we will design numerical discretizations that preserve key properties and that allow for whole organ simulations. To evaluate predictability, we will develop a new computational platform for model adaptivity and calibration. The project is multidisciplinary combining mathematics, mechanics, scientific computing, and physiology.
If successful, this project enables the first in silico studies of the brain's waterscape across scales. The new models would open up a new research field within computational neuroscience with ample opportunities for further mathematical and more applied study. The processes at hand are associated with neurodegenerative diseases e.g. dementia and with brain swelling caused by e.g. stroke. The Waterscales project will provide the field with a sorely needed, new avenue of investigation to understand these conditions, with tremendous long-term impact.
Summary
Your brain has its own waterscape: whether you are reading or sleeping, fluid flows through the brain tissue and clears waste in the process. These physiological processes are crucial for the well-being of the brain. In spite of their importance we understand them but little. Mathematics and numerics could play a crucial role in gaining new insight. Indeed, medical doctors express an urgent need for multiscale modeling of water transport through the brain, to overcome limitations in traditional techniques. Surprisingly little attention has been paid to the numerics of the brain's waterscape however, and fundamental knowledge is missing.
In response, the Waterscales ambition is to establish the mathematical and computational foundations for predictively modeling fluid flow and solute transport through the brain across scales -- from the cellular to the organ level. The project aims to bridge multiscale fluid mechanics and cellular electrophysiology to pioneer new families of mathematical models that couple macroscale, mesoscale and microscale flow with glial cell dynamics. For these models, we will design numerical discretizations that preserve key properties and that allow for whole organ simulations. To evaluate predictability, we will develop a new computational platform for model adaptivity and calibration. The project is multidisciplinary combining mathematics, mechanics, scientific computing, and physiology.
If successful, this project enables the first in silico studies of the brain's waterscape across scales. The new models would open up a new research field within computational neuroscience with ample opportunities for further mathematical and more applied study. The processes at hand are associated with neurodegenerative diseases e.g. dementia and with brain swelling caused by e.g. stroke. The Waterscales project will provide the field with a sorely needed, new avenue of investigation to understand these conditions, with tremendous long-term impact.
Max ERC Funding
1 500 000 €
Duration
Start date: 2017-04-01, End date: 2022-03-31
