Project acronym Active-DNA
Project Computationally Active DNA Nanostructures
Researcher (PI) Damien WOODS
Host Institution (HI) NATIONAL UNIVERSITY OF IRELAND MAYNOOTH
Call Details Consolidator Grant (CoG), PE6, ERC-2017-COG
Summary During the 20th century computer technology evolved from bulky, slow, special purpose mechanical engines to the now ubiquitous silicon chips and software that are one of the pinnacles of human ingenuity. The goal of the field of molecular programming is to take the next leap and build a new generation of matter-based computers using DNA, RNA and proteins. This will be accomplished by computer scientists, physicists and chemists designing molecules to execute ``wet'' nanoscale programs in test tubes. The workflow includes proposing theoretical models, mathematically proving their computational properties, physical modelling and implementation in the wet-lab.
The past decade has seen remarkable progress at building static 2D and 3D DNA nanostructures. However, unlike biological macromolecules and complexes that are built via specified self-assembly pathways, that execute robotic-like movements, and that undergo evolution, the activity of human-engineered nanostructures is severely limited. We will need sophisticated algorithmic ideas to build structures that rival active living systems. Active-DNA, aims to address this challenge by achieving a number of objectives on computation, DNA-based self-assembly and molecular robotics. Active-DNA research work will range from defining models and proving theorems that characterise the computational and expressive capabilities of such active programmable materials to experimental work implementing active DNA nanostructures in the wet-lab.
Summary
During the 20th century computer technology evolved from bulky, slow, special purpose mechanical engines to the now ubiquitous silicon chips and software that are one of the pinnacles of human ingenuity. The goal of the field of molecular programming is to take the next leap and build a new generation of matter-based computers using DNA, RNA and proteins. This will be accomplished by computer scientists, physicists and chemists designing molecules to execute ``wet'' nanoscale programs in test tubes. The workflow includes proposing theoretical models, mathematically proving their computational properties, physical modelling and implementation in the wet-lab.
The past decade has seen remarkable progress at building static 2D and 3D DNA nanostructures. However, unlike biological macromolecules and complexes that are built via specified self-assembly pathways, that execute robotic-like movements, and that undergo evolution, the activity of human-engineered nanostructures is severely limited. We will need sophisticated algorithmic ideas to build structures that rival active living systems. Active-DNA, aims to address this challenge by achieving a number of objectives on computation, DNA-based self-assembly and molecular robotics. Active-DNA research work will range from defining models and proving theorems that characterise the computational and expressive capabilities of such active programmable materials to experimental work implementing active DNA nanostructures in the wet-lab.
Max ERC Funding
2 349 603 €
Duration
Start date: 2018-11-01, End date: 2023-10-31
Project acronym ALGOA
Project Novel algorithm for treatment planning of patients with osteoarthritis
Researcher (PI) Rami Kristian KORHONEN
Host Institution (HI) ITA-SUOMEN YLIOPISTO
Call Details Proof of Concept (PoC), PC1, ERC-2016-PoC
Summary Osteoarthritis (OA) is a common joint disease affecting over 40 million Europeans. Most common consequences of OA are pain, disability and social isolation. What is alarming, the number of patients will increase 50% in developed countries during the next 20 years. Moreover, the economic costs of OA are considerable since 1) direct healthcare (hospital admissions, medical examinations, drug therapy, etc.) and 2) productivity costs due to reduced performance while at work and absence from work have been estimated to be between 1% and 2.5% of the gross domestic product (GDP) in Western countries.
We have developed an algorithm that is able to predict the progression of OA for overweight subjects while healthy subjects do not develop OA. When employed in clinical use, preventive and personalised treatments can be started before clinically significant symptoms are observed. This marks a major breakthrough in improving the life quality of OA patients and patients prone to OA. Our discovery will directly lead to longer working careers and lesser absence from work, and will result subsequently increased productivity. Moreover, the patients are expected to live longer due to reduced disability and social isolation.
Moreover, the discovery provides economic long-term relief for the health care system, which is burdened by increasing geriatric population and stringent economic environment. With our tool, as an example, by eliminating 25% of medical examinations annually due to overweight or obesity in Finland (150.000 patients), we estimate to decrease annual direct costs by 140M€ and indirect costs by 185M€.
In the PoC project we will carry out technical proof-of-concept and perform pre-commercialisation actions to shorten the time to market. The ultimate goal after the project is to develop our innovation towards a software product, aiding the OA diagnostics in hospitals and having commercialisation potential amongst medical device companies.
Summary
Osteoarthritis (OA) is a common joint disease affecting over 40 million Europeans. Most common consequences of OA are pain, disability and social isolation. What is alarming, the number of patients will increase 50% in developed countries during the next 20 years. Moreover, the economic costs of OA are considerable since 1) direct healthcare (hospital admissions, medical examinations, drug therapy, etc.) and 2) productivity costs due to reduced performance while at work and absence from work have been estimated to be between 1% and 2.5% of the gross domestic product (GDP) in Western countries.
We have developed an algorithm that is able to predict the progression of OA for overweight subjects while healthy subjects do not develop OA. When employed in clinical use, preventive and personalised treatments can be started before clinically significant symptoms are observed. This marks a major breakthrough in improving the life quality of OA patients and patients prone to OA. Our discovery will directly lead to longer working careers and lesser absence from work, and will result subsequently increased productivity. Moreover, the patients are expected to live longer due to reduced disability and social isolation.
Moreover, the discovery provides economic long-term relief for the health care system, which is burdened by increasing geriatric population and stringent economic environment. With our tool, as an example, by eliminating 25% of medical examinations annually due to overweight or obesity in Finland (150.000 patients), we estimate to decrease annual direct costs by 140M€ and indirect costs by 185M€.
In the PoC project we will carry out technical proof-of-concept and perform pre-commercialisation actions to shorten the time to market. The ultimate goal after the project is to develop our innovation towards a software product, aiding the OA diagnostics in hospitals and having commercialisation potential amongst medical device companies.
Max ERC Funding
150 000 €
Duration
Start date: 2018-01-01, End date: 2019-06-30
Project acronym ALGOCom
Project Novel Algorithmic Techniques through the Lens of Combinatorics
Researcher (PI) Parinya Chalermsook
Host Institution (HI) AALTO KORKEAKOULUSAATIO SR
Call Details Starting Grant (StG), PE6, ERC-2017-STG
Summary Real-world optimization problems pose major challenges to algorithmic research. For instance, (i) many important problems are believed to be intractable (i.e. NP-hard) and (ii) with the growth of data size, modern applications often require a decision making under {\em incomplete and dynamically changing input data}. After several decades of research, central problems in these domains have remained poorly understood (e.g. Is there an asymptotically most efficient binary search trees?) Existing algorithmic techniques either reach their limitation or are inherently tailored to special cases.
This project attempts to untangle this gap in the state of the art and seeks new interplay across multiple areas of algorithms, such as approximation algorithms, online algorithms, fixed-parameter tractable (FPT) algorithms, exponential time algorithms, and data structures. We propose new directions from the {\em structural perspectives} that connect the aforementioned algorithmic problems to basic questions in combinatorics.
Our approaches fall into one of the three broad schemes: (i) new structural theory, (ii) intermediate problems, and (iii) transfer of techniques. These directions partially build on the PI's successes in resolving more than ten classical problems in this context.
Resolving the proposed problems will likely revolutionize our understanding about algorithms and data structures and potentially unify techniques in multiple algorithmic regimes. Any progress is, in fact, already a significant contribution to the algorithms community. We suggest concrete intermediate goals that are of independent interest and have lower risks, so they are suitable for Ph.D students.
Summary
Real-world optimization problems pose major challenges to algorithmic research. For instance, (i) many important problems are believed to be intractable (i.e. NP-hard) and (ii) with the growth of data size, modern applications often require a decision making under {\em incomplete and dynamically changing input data}. After several decades of research, central problems in these domains have remained poorly understood (e.g. Is there an asymptotically most efficient binary search trees?) Existing algorithmic techniques either reach their limitation or are inherently tailored to special cases.
This project attempts to untangle this gap in the state of the art and seeks new interplay across multiple areas of algorithms, such as approximation algorithms, online algorithms, fixed-parameter tractable (FPT) algorithms, exponential time algorithms, and data structures. We propose new directions from the {\em structural perspectives} that connect the aforementioned algorithmic problems to basic questions in combinatorics.
Our approaches fall into one of the three broad schemes: (i) new structural theory, (ii) intermediate problems, and (iii) transfer of techniques. These directions partially build on the PI's successes in resolving more than ten classical problems in this context.
Resolving the proposed problems will likely revolutionize our understanding about algorithms and data structures and potentially unify techniques in multiple algorithmic regimes. Any progress is, in fact, already a significant contribution to the algorithms community. We suggest concrete intermediate goals that are of independent interest and have lower risks, so they are suitable for Ph.D students.
Max ERC Funding
1 411 258 €
Duration
Start date: 2018-02-01, End date: 2023-01-31
Project acronym Amitochondriates
Project Life without mitochondrion
Researcher (PI) Vladimir HAMPL
Host Institution (HI) UNIVERZITA KARLOVA
Call Details Consolidator Grant (CoG), LS8, ERC-2017-COG
Summary Mitochondria are often referred to as the “power houses” of eukaryotic cells. All eukaryotes were thought to have mitochondria of some form until 2016, when the first eukaryote thriving without mitochondria was discovered by our laboratory – a flagellate Monocercomonoides. Understanding cellular functions of these cells, which represent a new functional type of eukaryotes, and understanding the circumstances of the unique event of mitochondrial loss are motivations for this proposal. The first objective focuses on the cell physiology. We will perform a metabolomic study revealing major metabolic pathways and concentrate further on elucidating its unique system of iron-sulphur cluster assembly. In the second objective, we will investigate in details the unique case of mitochondrial loss. We will examine two additional potentially amitochondriate lineages by means of genomics and transcriptomics, conduct experiments simulating the moments of mitochondrial loss and try to induce the mitochondrial loss in vitro by knocking out or down genes for mitochondrial biogenesis. We have chosen Giardia intestinalis and Entamoeba histolytica as models for the latter experiments, because their mitochondria are already reduced to minimalistic “mitosomes” and because some genetic tools are already available for them. Successful mitochondrial knock-outs would enable us to study mitochondrial loss in ‘real time’ and in vivo. In the third objective, we will focus on transforming Monocercomonoides into a tractable laboratory model by developing methods of axenic cultivation and genetic manipulation. This will open new possibilities in the studies of this organism and create a cell culture representing an amitochondriate model for cell biological studies enabling the dissection of mitochondrial effects from those of other compartments. The team is composed of the laboratory of PI and eight invited experts and we hope it has the ability to address these challenging questions.
Summary
Mitochondria are often referred to as the “power houses” of eukaryotic cells. All eukaryotes were thought to have mitochondria of some form until 2016, when the first eukaryote thriving without mitochondria was discovered by our laboratory – a flagellate Monocercomonoides. Understanding cellular functions of these cells, which represent a new functional type of eukaryotes, and understanding the circumstances of the unique event of mitochondrial loss are motivations for this proposal. The first objective focuses on the cell physiology. We will perform a metabolomic study revealing major metabolic pathways and concentrate further on elucidating its unique system of iron-sulphur cluster assembly. In the second objective, we will investigate in details the unique case of mitochondrial loss. We will examine two additional potentially amitochondriate lineages by means of genomics and transcriptomics, conduct experiments simulating the moments of mitochondrial loss and try to induce the mitochondrial loss in vitro by knocking out or down genes for mitochondrial biogenesis. We have chosen Giardia intestinalis and Entamoeba histolytica as models for the latter experiments, because their mitochondria are already reduced to minimalistic “mitosomes” and because some genetic tools are already available for them. Successful mitochondrial knock-outs would enable us to study mitochondrial loss in ‘real time’ and in vivo. In the third objective, we will focus on transforming Monocercomonoides into a tractable laboratory model by developing methods of axenic cultivation and genetic manipulation. This will open new possibilities in the studies of this organism and create a cell culture representing an amitochondriate model for cell biological studies enabling the dissection of mitochondrial effects from those of other compartments. The team is composed of the laboratory of PI and eight invited experts and we hope it has the ability to address these challenging questions.
Max ERC Funding
1 935 500 €
Duration
Start date: 2018-05-01, End date: 2023-04-30
Project acronym ANCHOR
Project Articular cartilage regeneration through the recruitment of bone marrow derived mesenchymal stem cells into extracelluar matrix derived scaffolds anchored by 3D printed polymeric supports
Researcher (PI) Daniel KELLY
Host Institution (HI) THE PROVOST, FELLOWS, FOUNDATION SCHOLARS & THE OTHER MEMBERS OF BOARD OF THE COLLEGE OF THE HOLY & UNDIVIDED TRINITY OF QUEEN ELIZABETH NEAR DUBLIN
Call Details Proof of Concept (PoC), ERC-2017-PoC
Summary Osteoarthritis (OA), the most common form of arthritis, is a serious disease of the joints affecting nearly 10% of the population worldwide. The onset of OA has been associated with defects to articular cartilage that lines the bones of synovial joints. Current strategies to treat articular cartilage defects are ineffective and/or prohibitively expensive. The aim of ANCHOR is to develop and commercialise a new medicinal product for articular cartilage regeneration that recruits endogenous bone marrow derived stem cells into an extracellular matrix derived scaffold anchored to the subchondral bone by 3D printed polymeric supports. By recruiting endogenous cells into a supporting scaffold, ANCHOR will obviate the need for pre-seeding scaffolds with cells prior to implantation into cartilage defects, thereby dramatically reducing the cost and complexity of the repair procedure. It will also overcome the need for suturing of a scaffold into a cartilage defect, which is a very time consuming and technically challenging surgical procedure. Finally, the inherent chondro-inductivity of the cartilage ECM derived scaffolds developed by the applicant will maximise the potential for hyaline cartilage regeneration. The project will leverage the applicants extensive experience in ECM derived biomaterials and 3D printing to develop a new product with significant commercial potential. The impact of ANCHOR will be multi-faceted: it will transform how damaged joints are treated by orthopaedic surgeons, it will create economic value through the commercialization of IP, and most importantly it will improve patient experience and their long-term health and well-being.
Summary
Osteoarthritis (OA), the most common form of arthritis, is a serious disease of the joints affecting nearly 10% of the population worldwide. The onset of OA has been associated with defects to articular cartilage that lines the bones of synovial joints. Current strategies to treat articular cartilage defects are ineffective and/or prohibitively expensive. The aim of ANCHOR is to develop and commercialise a new medicinal product for articular cartilage regeneration that recruits endogenous bone marrow derived stem cells into an extracellular matrix derived scaffold anchored to the subchondral bone by 3D printed polymeric supports. By recruiting endogenous cells into a supporting scaffold, ANCHOR will obviate the need for pre-seeding scaffolds with cells prior to implantation into cartilage defects, thereby dramatically reducing the cost and complexity of the repair procedure. It will also overcome the need for suturing of a scaffold into a cartilage defect, which is a very time consuming and technically challenging surgical procedure. Finally, the inherent chondro-inductivity of the cartilage ECM derived scaffolds developed by the applicant will maximise the potential for hyaline cartilage regeneration. The project will leverage the applicants extensive experience in ECM derived biomaterials and 3D printing to develop a new product with significant commercial potential. The impact of ANCHOR will be multi-faceted: it will transform how damaged joints are treated by orthopaedic surgeons, it will create economic value through the commercialization of IP, and most importantly it will improve patient experience and their long-term health and well-being.
Max ERC Funding
149 945 €
Duration
Start date: 2018-01-01, End date: 2019-06-30
Project acronym ANEMONE
Project Antibiofouling Nanopatterned Electrospun Membranes for Nanofiltration Applications
Researcher (PI) Eoin CASEY
Host Institution (HI) UNIVERSITY COLLEGE DUBLIN, NATIONAL UNIVERSITY OF IRELAND, DUBLIN
Call Details Proof of Concept (PoC), ERC-2017-PoC
Summary Water-stress in an increasing global problem and solutions such as water recycling and seawater desalination are now
becoming a necessary part of the water infrastructure. The technology for the production of safe drinking is increasingly
dependent on these more diverse sources and a key enabling technology is membrane filtration. While membrane system
are effective, the operating costs of such systems are hampered by fouling which increases the energy requirement for
process operation. The unique idea of this Proof of Concept is to develop an electrospun nanostructured membrane which
can be integrated into water filtration technologies. The unique method of fabrication will produce an inherently antibacterial
and antibiofouling surface in a one-step process, cutting the number of manufacturing steps. This concept, when deployed
commercially is expected to dramatically reduce the operating costs of membrane processes for water treatment. The
commercialisation route of the product will be through the patent protection and the licensing of the technology with a view
to rapid commercialisation.
Summary
Water-stress in an increasing global problem and solutions such as water recycling and seawater desalination are now
becoming a necessary part of the water infrastructure. The technology for the production of safe drinking is increasingly
dependent on these more diverse sources and a key enabling technology is membrane filtration. While membrane system
are effective, the operating costs of such systems are hampered by fouling which increases the energy requirement for
process operation. The unique idea of this Proof of Concept is to develop an electrospun nanostructured membrane which
can be integrated into water filtration technologies. The unique method of fabrication will produce an inherently antibacterial
and antibiofouling surface in a one-step process, cutting the number of manufacturing steps. This concept, when deployed
commercially is expected to dramatically reduce the operating costs of membrane processes for water treatment. The
commercialisation route of the product will be through the patent protection and the licensing of the technology with a view
to rapid commercialisation.
Max ERC Funding
148 805 €
Duration
Start date: 2017-10-01, End date: 2019-03-31
Project acronym ANTILEAK
Project Development of antagonists of vascular leakage
Researcher (PI) Pipsa SAHARINEN
Host Institution (HI) HELSINGIN YLIOPISTO
Call Details Consolidator Grant (CoG), LS4, ERC-2017-COG
Summary Dysregulation of capillary permeability is a severe problem in critically ill patients, but the mechanisms involved are poorly understood. Further, there are no targeted therapies to stabilize leaky vessels in various common, potentially fatal diseases, such as systemic inflammation and sepsis, which affect millions of people annually. Although a multitude of signals that stimulate opening of endothelial cell-cell junctions leading to permeability have been characterized using cellular and in vivo models, approaches to reverse the harmful process of capillary leakage in disease conditions are yet to be identified. I propose to explore a novel autocrine endothelial permeability regulatory system as a potentially universal mechanism that antagonizes vascular stabilizing ques and sustains vascular leakage in inflammation. My group has identified inflammation-induced mechanisms that switch vascular stabilizing factors into molecules that destabilize vascular barriers, and identified tools to prevent the barrier disruption. Building on these discoveries, my group will use mouse genetics, structural biology and innovative, systematic antibody development coupled with gene editing and gene silencing technology, in order to elucidate mechanisms of vascular barrier breakdown and repair in systemic inflammation. The expected outcomes include insights into endothelial cell signaling and permeability regulation, and preclinical proof-of-concept antibodies to control endothelial activation and vascular leakage in systemic inflammation and sepsis models. Ultimately, the new knowledge and preclinical tools developed in this project may facilitate future development of targeted approaches against vascular leakage.
Summary
Dysregulation of capillary permeability is a severe problem in critically ill patients, but the mechanisms involved are poorly understood. Further, there are no targeted therapies to stabilize leaky vessels in various common, potentially fatal diseases, such as systemic inflammation and sepsis, which affect millions of people annually. Although a multitude of signals that stimulate opening of endothelial cell-cell junctions leading to permeability have been characterized using cellular and in vivo models, approaches to reverse the harmful process of capillary leakage in disease conditions are yet to be identified. I propose to explore a novel autocrine endothelial permeability regulatory system as a potentially universal mechanism that antagonizes vascular stabilizing ques and sustains vascular leakage in inflammation. My group has identified inflammation-induced mechanisms that switch vascular stabilizing factors into molecules that destabilize vascular barriers, and identified tools to prevent the barrier disruption. Building on these discoveries, my group will use mouse genetics, structural biology and innovative, systematic antibody development coupled with gene editing and gene silencing technology, in order to elucidate mechanisms of vascular barrier breakdown and repair in systemic inflammation. The expected outcomes include insights into endothelial cell signaling and permeability regulation, and preclinical proof-of-concept antibodies to control endothelial activation and vascular leakage in systemic inflammation and sepsis models. Ultimately, the new knowledge and preclinical tools developed in this project may facilitate future development of targeted approaches against vascular leakage.
Max ERC Funding
1 999 770 €
Duration
Start date: 2018-05-01, End date: 2023-04-30
Project acronym APES
Project Accuracy and precision for molecular solids
Researcher (PI) Jiri KLIMES
Host Institution (HI) UNIVERZITA KARLOVA
Call Details Starting Grant (StG), PE4, ERC-2017-STG
Summary The description of high pressure phases or polymorphism of molecular solids represents a significant scientific challenge both for experiment and theory. Theoretical methods that are currently used struggle to describe the tiny energy differences between different phases. It is the aim of this project to develop a scheme that would allow accurate and reliable predictions of the binding energies of molecular solids and of the energy differences between different phases.
To reach the required accuracy, we will combine the coupled cluster approach, widely used for reference quality calculations for molecules, with the random phase approximation (RPA) within periodic boundary conditions. As I have recently shown, RPA-based approaches are already some of the most accurate and practically usable methods for the description of extended systems. However, reliability is not only a question of accuracy. Reliable data need to be precise, that is, converged with the numerical parameters so that they are reproducible by other researchers.
Reproducibility is already a growing concern in the field. It is likely to become a considerable issue for highly accurate methods as the calculated energies have a stronger dependence on the simulation parameters such as the basis set size. Two main approaches will be explored to assure precision. First, we will develop the so-called asymptotic correction scheme to speed-up the convergence of the correlation energies with the basis set size. Second, we will directly compare the lattice energies from periodic and finite cluster based calculations. Both should yield identical answers, but if and how the agreement can be reached for general system is currently far from being understood for methods such as coupled cluster. Reliable data will allow us to answer some of the open questions regarding the stability of polymorphs and high pressure phases, such as the possibility of existence of high pressure ionic phases of water and ammonia.
Summary
The description of high pressure phases or polymorphism of molecular solids represents a significant scientific challenge both for experiment and theory. Theoretical methods that are currently used struggle to describe the tiny energy differences between different phases. It is the aim of this project to develop a scheme that would allow accurate and reliable predictions of the binding energies of molecular solids and of the energy differences between different phases.
To reach the required accuracy, we will combine the coupled cluster approach, widely used for reference quality calculations for molecules, with the random phase approximation (RPA) within periodic boundary conditions. As I have recently shown, RPA-based approaches are already some of the most accurate and practically usable methods for the description of extended systems. However, reliability is not only a question of accuracy. Reliable data need to be precise, that is, converged with the numerical parameters so that they are reproducible by other researchers.
Reproducibility is already a growing concern in the field. It is likely to become a considerable issue for highly accurate methods as the calculated energies have a stronger dependence on the simulation parameters such as the basis set size. Two main approaches will be explored to assure precision. First, we will develop the so-called asymptotic correction scheme to speed-up the convergence of the correlation energies with the basis set size. Second, we will directly compare the lattice energies from periodic and finite cluster based calculations. Both should yield identical answers, but if and how the agreement can be reached for general system is currently far from being understood for methods such as coupled cluster. Reliable data will allow us to answer some of the open questions regarding the stability of polymorphs and high pressure phases, such as the possibility of existence of high pressure ionic phases of water and ammonia.
Max ERC Funding
924 375 €
Duration
Start date: 2018-01-01, End date: 2022-12-31
Project acronym ATM-GTP
Project Atmospheric Gas-to-Particle conversion
Researcher (PI) Markku KULMALA
Host Institution (HI) HELSINGIN YLIOPISTO
Call Details Advanced Grant (AdG), PE10, ERC-2016-ADG
Summary Atmospheric Gas-to-Particle conversion (ATM-GTP) is a 5-year project focusing on one of the most critical atmospheric processes relevant to global climate and air quality: the first steps of atmospheric aerosol particle formation and growth. The project will concentrate on the currently lacking environmentally-specific knowledge about the interacting, non-linear, physical and chemical atmospheric processes associated with nano-scale gas-to-particle conversion (GTP). The main scientific objective of ATM-GTP is to create a deep understanding on atmospheric GTP taking place at the sub-5 nm size range, particularly in heavily-polluted Chinese mega cities like Beijing and in pristine environments like Siberia and Nordic high-latitude regions. We also aim to find out how nano-GTM is associated with air quality-climate interactions and feedbacks. We are interested in quantifying the effect of nano-GTP on the COBACC (Continental Biosphere-Aerosol-Cloud-Climate) feedback loop that is important in Arctic and boreal regions. Our approach enables to point out the effective reduction mechanisms of the secondary air pollution by a factor of 5-10 and to make reliable estimates of the global and regional aerosol loads, including anthropogenic and biogenic contributions to these loads. We can estimate the future role of Northern Hemispheric biosphere in reducing the global radiative forcing via the quantified feedbacks. The project is carried out by the world-leading scientist in atmospheric aerosol science, being also one of the founders of terrestrial ecosystem meteorology, together with his research team. The project uses novel infrastructures including SMEAR (Stations Measuring Ecosystem Atmospheric Relations) stations, related modelling platforms and regional data from Russia and China. The work will be carried out in synergy with several national, Nordic and EU research-innovation projects: Finnish Center of Excellence-ATM, Nordic CoE-CRAICC and EU-FP7-BACCHUS.
Summary
Atmospheric Gas-to-Particle conversion (ATM-GTP) is a 5-year project focusing on one of the most critical atmospheric processes relevant to global climate and air quality: the first steps of atmospheric aerosol particle formation and growth. The project will concentrate on the currently lacking environmentally-specific knowledge about the interacting, non-linear, physical and chemical atmospheric processes associated with nano-scale gas-to-particle conversion (GTP). The main scientific objective of ATM-GTP is to create a deep understanding on atmospheric GTP taking place at the sub-5 nm size range, particularly in heavily-polluted Chinese mega cities like Beijing and in pristine environments like Siberia and Nordic high-latitude regions. We also aim to find out how nano-GTM is associated with air quality-climate interactions and feedbacks. We are interested in quantifying the effect of nano-GTP on the COBACC (Continental Biosphere-Aerosol-Cloud-Climate) feedback loop that is important in Arctic and boreal regions. Our approach enables to point out the effective reduction mechanisms of the secondary air pollution by a factor of 5-10 and to make reliable estimates of the global and regional aerosol loads, including anthropogenic and biogenic contributions to these loads. We can estimate the future role of Northern Hemispheric biosphere in reducing the global radiative forcing via the quantified feedbacks. The project is carried out by the world-leading scientist in atmospheric aerosol science, being also one of the founders of terrestrial ecosystem meteorology, together with his research team. The project uses novel infrastructures including SMEAR (Stations Measuring Ecosystem Atmospheric Relations) stations, related modelling platforms and regional data from Russia and China. The work will be carried out in synergy with several national, Nordic and EU research-innovation projects: Finnish Center of Excellence-ATM, Nordic CoE-CRAICC and EU-FP7-BACCHUS.
Max ERC Funding
2 500 000 €
Duration
Start date: 2017-06-01, End date: 2022-05-31
Project acronym BEHAVFRICTIONS
Project Behavioral Implications of Information-Processing Frictions
Researcher (PI) Jakub STEINER
Host Institution (HI) NARODOHOSPODARSKY USTAV AKADEMIE VED CESKE REPUBLIKY VEREJNA VYZKUMNA INSTITUCE
Call Details Consolidator Grant (CoG), SH1, ERC-2017-COG
Summary BEHAVFRICTIONS will use novel models focussing on information-processing frictions to explain choice patterns described in behavioral economics and psychology. The proposed research will provide microfoundations that are essential for (i) identification of stable preferences, (ii) counterfactual predictions, and (iii) normative conclusions.
(i) Agents who face information-processing costs must trade the precision of choice against information costs. Their behavior thus reflects both their stable preferences and the context-dependent procedures that manage their errors stemming from imperfect information processing. In the absence of micro-founded models, the two drivers of the behavior are difficult to disentangle for outside observers. In some pillars of the proposal, the agents follow choice rules that closely resemble logit rules used in structural estimation. This will allow me to reinterpret the structural estimation fits to choice data and to make a distinction between the stable preferences and frictions.
(ii) Such a distinction is important in counterfactual policy analysis because the second-best decision procedures that manage the errors in choice are affected by the analysed policy. Incorporation of the information-processing frictions into existing empirical methods will improve our ability to predict effects of the policies.
(iii) My preliminary results suggest that when an agent is prone to committing errors, biases--such as overconfidence, confirmatory bias, or perception biases known from prospect theory--arise under second-best strategies. By providing the link between the agent's environment and the second-best distribution of the perception errors, my models will delineate environments in which these biases shield the agents from the most costly mistakes from environments in which the biases turn into maladaptations. The distinction will inform the normative debate on debiasing.
Summary
BEHAVFRICTIONS will use novel models focussing on information-processing frictions to explain choice patterns described in behavioral economics and psychology. The proposed research will provide microfoundations that are essential for (i) identification of stable preferences, (ii) counterfactual predictions, and (iii) normative conclusions.
(i) Agents who face information-processing costs must trade the precision of choice against information costs. Their behavior thus reflects both their stable preferences and the context-dependent procedures that manage their errors stemming from imperfect information processing. In the absence of micro-founded models, the two drivers of the behavior are difficult to disentangle for outside observers. In some pillars of the proposal, the agents follow choice rules that closely resemble logit rules used in structural estimation. This will allow me to reinterpret the structural estimation fits to choice data and to make a distinction between the stable preferences and frictions.
(ii) Such a distinction is important in counterfactual policy analysis because the second-best decision procedures that manage the errors in choice are affected by the analysed policy. Incorporation of the information-processing frictions into existing empirical methods will improve our ability to predict effects of the policies.
(iii) My preliminary results suggest that when an agent is prone to committing errors, biases--such as overconfidence, confirmatory bias, or perception biases known from prospect theory--arise under second-best strategies. By providing the link between the agent's environment and the second-best distribution of the perception errors, my models will delineate environments in which these biases shield the agents from the most costly mistakes from environments in which the biases turn into maladaptations. The distinction will inform the normative debate on debiasing.
Max ERC Funding
1 321 488 €
Duration
Start date: 2018-06-01, End date: 2023-05-31
