Project acronym 3DSCAN
Project Commercialisation of novel ultra-fast 3D laser scanning technology
Researcher (PI) Robin Angus SILVER
Host Institution (HI) UNIVERSITY COLLEGE LONDON
Country United Kingdom
Call Details Proof of Concept (PoC), ERC-2019-PoC
Summary Understanding how the brain processes information is one of the unsolved grand challenges in science. Moreover, neurological disorders, which disrupt information processing, have an enormous societal and economic impact. Studying information processing in the brain requires measurements of signals as they flow through neural circuits. However, the 3D nature of brain circuits and the speed of information transfer makes it difficult for neuroscientists to measure their properties with sufficiently high spatial and temporal resolution. During the NEUROGAIN ERC project, we developed a novel type of Acousto-Optic Lens (AOL)-based high-speed 3D laser scanner. This technology enables the focusing and scanning of a laser beam at 20-40 kHz. This scanning technology can be added to existing two-photon microscopes to enable 3D imaging of neurons and circuits with unprecedented spatio-temporal resolution. Moreover, it also automatically corrects for brain movement in real-time providing sharper images. This ERC PoC will facilitate commercialization of this 3D scanning technology by providing support to explore the markets in biosciences and beyond, protect the IP and facilitate early stage manufacture and assembly of AOL 3D scanners to supply biomedical researchers.
Summary
Understanding how the brain processes information is one of the unsolved grand challenges in science. Moreover, neurological disorders, which disrupt information processing, have an enormous societal and economic impact. Studying information processing in the brain requires measurements of signals as they flow through neural circuits. However, the 3D nature of brain circuits and the speed of information transfer makes it difficult for neuroscientists to measure their properties with sufficiently high spatial and temporal resolution. During the NEUROGAIN ERC project, we developed a novel type of Acousto-Optic Lens (AOL)-based high-speed 3D laser scanner. This technology enables the focusing and scanning of a laser beam at 20-40 kHz. This scanning technology can be added to existing two-photon microscopes to enable 3D imaging of neurons and circuits with unprecedented spatio-temporal resolution. Moreover, it also automatically corrects for brain movement in real-time providing sharper images. This ERC PoC will facilitate commercialization of this 3D scanning technology by providing support to explore the markets in biosciences and beyond, protect the IP and facilitate early stage manufacture and assembly of AOL 3D scanners to supply biomedical researchers.
Max ERC Funding
150 000 €
Duration
Start date: 2019-06-01, End date: 2020-11-30
Project acronym [LC]2
Project 'Living' Colloidal Liquid Crystals
Researcher (PI) Tyler Shendruk
Host Institution (HI) THE UNIVERSITY OF EDINBURGH
Country United Kingdom
Call Details Starting Grant (StG), PE3, ERC-2019-STG
Summary We propose an unprecedented class of soft, self-assembled and self-motile micro-machines. The combined qualities of active fluids and colloidal liquid crystals can be leveraged to design intrinsically out-of- equilibrium hierarchal structures, or ‘Living’ Colloidal Liquid Crystals [LC]2. The study of colloidal interactions and self-assembly in active nematics has yet to be considered and constitutes an unexplored and inter-disciplinary application of the emerging sciences of active matter and colloidal liquid crystals. Activity will endow dynamical multi-scale colloidal structures with autonomous functionality, including self-motility, self-revolution and dynamical self-transformations, which are exactly the characteristics one would desire for a first generation of autonomous components of micro-biomechanical systems and soft micro-machines. As hybrids between biological active fluids and man-made materials, [LC]2 structures represent an early foray into ‘living’ metamaterials, in which active self-assembly of simple components produces a rich diversity of behaviours and the potential for autonomously tunable material properties, mimicking biological complexity. In particular, we hypothesize self-assembled [LC]2 dimer turbines, colloidal flagella and ant-like group retrieval. These systems represent a fundamentally innovative concept that we propose to drive nanotechnology into a new future of soft materials that biomimetically self-assemble and autonomously enact functions. It is our multiscale coarse-grained simulations and expertise in flowing active nematic fluids that generates the opportunity for this unique line of research.
Summary
We propose an unprecedented class of soft, self-assembled and self-motile micro-machines. The combined qualities of active fluids and colloidal liquid crystals can be leveraged to design intrinsically out-of- equilibrium hierarchal structures, or ‘Living’ Colloidal Liquid Crystals [LC]2. The study of colloidal interactions and self-assembly in active nematics has yet to be considered and constitutes an unexplored and inter-disciplinary application of the emerging sciences of active matter and colloidal liquid crystals. Activity will endow dynamical multi-scale colloidal structures with autonomous functionality, including self-motility, self-revolution and dynamical self-transformations, which are exactly the characteristics one would desire for a first generation of autonomous components of micro-biomechanical systems and soft micro-machines. As hybrids between biological active fluids and man-made materials, [LC]2 structures represent an early foray into ‘living’ metamaterials, in which active self-assembly of simple components produces a rich diversity of behaviours and the potential for autonomously tunable material properties, mimicking biological complexity. In particular, we hypothesize self-assembled [LC]2 dimer turbines, colloidal flagella and ant-like group retrieval. These systems represent a fundamentally innovative concept that we propose to drive nanotechnology into a new future of soft materials that biomimetically self-assemble and autonomously enact functions. It is our multiscale coarse-grained simulations and expertise in flowing active nematic fluids that generates the opportunity for this unique line of research.
Max ERC Funding
1 402 345 €
Duration
Start date: 2019-12-01, End date: 2024-11-30
Project acronym ABOLED
Project Commercial feasibility of an anti-bacterial treatment
Researcher (PI) Ifor SAMUEL
Host Institution (HI) THE UNIVERSITY COURT OF THE UNIVERSITY OF ST ANDREWS
Country United Kingdom
Call Details Proof of Concept (PoC), ERC-2019-PoC
Summary Multidrug resistance of pathogenic bacteria has become a serious threat to public health. The need to develop novel technologies to combat the evolution of bacterial drug resistance is clearly a matter of public concern and urgency. The consequences of AMR include (i) reducing our ability to treat common infectious, resulting in prolonged illness and a greater risk of complications; (ii) patients remaining infectious for longer due to ineffective treatments, making them more likely to pass infections on to others; (iii) compromising advances in modern medicine (such as organ transplantation or chemotherapy) due to risk of infection; and (iv) increasing economic burden on health care systems, families, and societies. This project aims to assess the commercial viability of an alternative approach to this problem.
Summary
Multidrug resistance of pathogenic bacteria has become a serious threat to public health. The need to develop novel technologies to combat the evolution of bacterial drug resistance is clearly a matter of public concern and urgency. The consequences of AMR include (i) reducing our ability to treat common infectious, resulting in prolonged illness and a greater risk of complications; (ii) patients remaining infectious for longer due to ineffective treatments, making them more likely to pass infections on to others; (iii) compromising advances in modern medicine (such as organ transplantation or chemotherapy) due to risk of infection; and (iv) increasing economic burden on health care systems, families, and societies. This project aims to assess the commercial viability of an alternative approach to this problem.
Max ERC Funding
150 000 €
Duration
Start date: 2019-08-01, End date: 2021-07-31
Project acronym AFRAB
Project African Abolitionism: The Rise and Transformations of Anti-Slavery in Africa
Researcher (PI) Benedetta ROSSI
Host Institution (HI) UNIVERSITY COLLEGE LONDON
Country United Kingdom
Call Details Advanced Grant (AdG), SH6, ERC-2019-ADG
Summary The historiography of Euro-American abolitionism is so vast that it has a history of its own (Brown 2006). By contrast, research on African abolitionism is a narrow field focused primarily on European anti-slavery activities. It presupposes that when Europe abolished slavery in Africa, Africans became abolitionists. This conclusion is unfounded. Many general questions have never been asked: When and where did African abolitionist movements develop? Who are the main ideologues of African abolitionism? How did abolitionism spread, among which groups? What forms of political struggle did African anti-slavery give rise to? While individual African abolitionists and regional movements have attracted limited attention, there is no major review of the phenomenon on a continental scale. AFRAB fills this gap. It contributes to African and global history and slavery studies by analyzing and comparing African abolitionist ideas and anti-slavery movements, the long-term consequences of European abolitionism, and the resilience of pro-slavery discourses.
Summary
The historiography of Euro-American abolitionism is so vast that it has a history of its own (Brown 2006). By contrast, research on African abolitionism is a narrow field focused primarily on European anti-slavery activities. It presupposes that when Europe abolished slavery in Africa, Africans became abolitionists. This conclusion is unfounded. Many general questions have never been asked: When and where did African abolitionist movements develop? Who are the main ideologues of African abolitionism? How did abolitionism spread, among which groups? What forms of political struggle did African anti-slavery give rise to? While individual African abolitionists and regional movements have attracted limited attention, there is no major review of the phenomenon on a continental scale. AFRAB fills this gap. It contributes to African and global history and slavery studies by analyzing and comparing African abolitionist ideas and anti-slavery movements, the long-term consequences of European abolitionism, and the resilience of pro-slavery discourses.
Max ERC Funding
2 499 951 €
Duration
Start date: 2020-10-01, End date: 2025-09-30
Project acronym AGRICON
Project Ancient genomic reconstruction of convergent evolution to agriculture
Researcher (PI) Pontus Rickard Otto Peter Skoglund
Host Institution (HI) THE FRANCIS CRICK INSTITUTE LIMITED
Country United Kingdom
Call Details Starting Grant (StG), LS8, ERC-2019-STG
Summary As global climates warmed ca. 10,000 years ago came a remarkable convergent transformation of human lifestyles that occurred independently in multiple continents and human populations. This transition from hunter-gatherer subsistence to food-production catalysed large-scale population growth, offering the opportunity for increased rates of adaptation, but also rapidly presented a large number of independent human populations with a new evolutionary challenge. This project will use ancient population genomics—the only way to directly reconstruct human genetic evolution—to study whether evolutionary processes during the agricultural transition differed in differed regions. Which genomic adaptations were associated with the agricultural transition? Did adaptation to hunter-gatherer and agricultural lifestyles act on similar genetic architecture in different instances? To which extent did adaptation in domestic dogs—the only species domesticated prior to the agricultural transition—occur in convergence with humans? To answer these questions, the project will generate ancient genomic data from pre-agricultural and early agricultural populations from multiple human- and domestic dog populations from Africa, Central America, and Southeast Asia. This will be achieved with direct sequencing as well as a new human ~850,000 SNP capture panel designed to avoid bias towards Eurasian ancestry. We will also develop new computational methods robust to the challenges posed by ancient genomes to identify adaptive admixture, analyse copy number variation, test continuous population models, and statistically assess convergence in the genomic architecture of adaptation. Leveraging cutting-edge ancient genomics and two model organisms for the genomic basis of phenotypic variation, this project aims to reconstruct the universal evolutionary phenomena underpinning a watershed evolutionary episode that shapes global biodiversity and the human condition to this day.
Summary
As global climates warmed ca. 10,000 years ago came a remarkable convergent transformation of human lifestyles that occurred independently in multiple continents and human populations. This transition from hunter-gatherer subsistence to food-production catalysed large-scale population growth, offering the opportunity for increased rates of adaptation, but also rapidly presented a large number of independent human populations with a new evolutionary challenge. This project will use ancient population genomics—the only way to directly reconstruct human genetic evolution—to study whether evolutionary processes during the agricultural transition differed in differed regions. Which genomic adaptations were associated with the agricultural transition? Did adaptation to hunter-gatherer and agricultural lifestyles act on similar genetic architecture in different instances? To which extent did adaptation in domestic dogs—the only species domesticated prior to the agricultural transition—occur in convergence with humans? To answer these questions, the project will generate ancient genomic data from pre-agricultural and early agricultural populations from multiple human- and domestic dog populations from Africa, Central America, and Southeast Asia. This will be achieved with direct sequencing as well as a new human ~850,000 SNP capture panel designed to avoid bias towards Eurasian ancestry. We will also develop new computational methods robust to the challenges posed by ancient genomes to identify adaptive admixture, analyse copy number variation, test continuous population models, and statistically assess convergence in the genomic architecture of adaptation. Leveraging cutting-edge ancient genomics and two model organisms for the genomic basis of phenotypic variation, this project aims to reconstruct the universal evolutionary phenomena underpinning a watershed evolutionary episode that shapes global biodiversity and the human condition to this day.
Max ERC Funding
1 500 000 €
Duration
Start date: 2019-11-01, End date: 2024-10-31
Project acronym ALGOSOC
Project Algorithmic Societies: Ethical Life in the Machine Learning Age
Researcher (PI) Louise Jane Amoore
Host Institution (HI) UNIVERSITY OF DURHAM
Country United Kingdom
Call Details Advanced Grant (AdG), SH2, ERC-2019-ADG
Summary ALGOSOC develops a new approach to understanding and responding to the consequences of machine learning algorithms for contemporary societies. Rapid advancements in machine learning technologies are transforming social and political life in ways that uniquely challenge how we live in relation to others. The life chances of a person are now intimately connected to the attributes that an algorithm has learned from the data patterns of unknown others. From judgements in the criminal justice system to decisions on treatment pathways in health, the outputs of algorithms have become pivotal to the decisions and adjudications on the probable futures of individuals. While there is substantial academic and public emphasis on defining ethical codes of conduct for algorithmic decisions, there is a lack of attention to how machine learning algorithms remake the ethical relations that define a society. In short, existing research is focused on limiting the harms of the actions of algorithms, whereas ALGOSOC focuses on how algorithms are redefining the thresholds of what harmful, good, bad, or risky behaviour means in a society. The ALGOSOC project will examine how 21st century machine learning algorithms are learning to recognize, to attribute, and to infer the characteristics of entities (people, groups, and objects). In order to do this, the project will conduct a series of path-defining studies of societal domains of machine learning that, though they share algorithms in common, have not previously been researched in combination: behavioural biometrics and biomedical object recognition; consumer recommendation and criminal justice scoring; oncology treatment pathways and anomaly detection for security. The ALGOSOC project will provide new social science knowledge of what is taking place as machine learning algorithms travel across different domains and sites, and how precisely they learn by their exposure to different worlds of data.
Summary
ALGOSOC develops a new approach to understanding and responding to the consequences of machine learning algorithms for contemporary societies. Rapid advancements in machine learning technologies are transforming social and political life in ways that uniquely challenge how we live in relation to others. The life chances of a person are now intimately connected to the attributes that an algorithm has learned from the data patterns of unknown others. From judgements in the criminal justice system to decisions on treatment pathways in health, the outputs of algorithms have become pivotal to the decisions and adjudications on the probable futures of individuals. While there is substantial academic and public emphasis on defining ethical codes of conduct for algorithmic decisions, there is a lack of attention to how machine learning algorithms remake the ethical relations that define a society. In short, existing research is focused on limiting the harms of the actions of algorithms, whereas ALGOSOC focuses on how algorithms are redefining the thresholds of what harmful, good, bad, or risky behaviour means in a society. The ALGOSOC project will examine how 21st century machine learning algorithms are learning to recognize, to attribute, and to infer the characteristics of entities (people, groups, and objects). In order to do this, the project will conduct a series of path-defining studies of societal domains of machine learning that, though they share algorithms in common, have not previously been researched in combination: behavioural biometrics and biomedical object recognition; consumer recommendation and criminal justice scoring; oncology treatment pathways and anomaly detection for security. The ALGOSOC project will provide new social science knowledge of what is taking place as machine learning algorithms travel across different domains and sites, and how precisely they learn by their exposure to different worlds of data.
Max ERC Funding
2 150 686 €
Duration
Start date: 2020-10-01, End date: 2025-09-30
Project acronym ANCESTORS
Project Making Ancestors: The Politics of Death in Prehistoric Europe
Researcher (PI) John ROBB
Host Institution (HI) THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE
Country United Kingdom
Call Details Advanced Grant (AdG), SH6, ERC-2019-ADG
Summary How did politics and inequality work in prehistoric Europe? Traditionally, politics has been seen in terms of discrete political ranks identified through differential treatment of individual burials. But this results in classifying much of prehistory, where the dead were treated in ways which effaced individual identity, as egalitarian. The result is an artificially dichotomous history: Neolithic people had landscapes, rituals and ancestors, Bronze and Iron Age people had politics and inequality. In the last two decades this approach has been strongly critiqued. Burial treatment rarely relates to status so directly; the dead serve many different political roles. Inequality in pre-state groups rarely consists of clear strata; inequality and equality exist in tension within groups. Inequality may have been present throughout European prehistory, but manifest situationally through differential life chances, kinship, ritual or ancestorhood, rather than overtly through political command, wealth or identity. But this new perspective has never been tested empirically.
This project tests alternative models of prehistoric inequality and deathways. To investigate social relations in life, it uses osteobiography, reconstructing life stories from skeletons through scientific data on identity, health, diet, mobility and kinship. To understand deathways, it employs a second new methodology, funerary taphonomy. Combining osteobiography and taphonomy allows us to connect ancient lives and deaths. Peninsular Italy provides a substantial test sequence typical of much of Europe. For each of three key periods (Neolithic, 6000-4000 BC; Final Neolithic to Early Bronze Age, 4000-1800 BC; Middle Bronze Age to Iron Age, 1800-600 BC), 200+ individuals will be analysed. The results will allow us to evaluate for the first time how inequality affected lives in prehistoric Europe and what role ancestors played in it.
Summary
How did politics and inequality work in prehistoric Europe? Traditionally, politics has been seen in terms of discrete political ranks identified through differential treatment of individual burials. But this results in classifying much of prehistory, where the dead were treated in ways which effaced individual identity, as egalitarian. The result is an artificially dichotomous history: Neolithic people had landscapes, rituals and ancestors, Bronze and Iron Age people had politics and inequality. In the last two decades this approach has been strongly critiqued. Burial treatment rarely relates to status so directly; the dead serve many different political roles. Inequality in pre-state groups rarely consists of clear strata; inequality and equality exist in tension within groups. Inequality may have been present throughout European prehistory, but manifest situationally through differential life chances, kinship, ritual or ancestorhood, rather than overtly through political command, wealth or identity. But this new perspective has never been tested empirically.
This project tests alternative models of prehistoric inequality and deathways. To investigate social relations in life, it uses osteobiography, reconstructing life stories from skeletons through scientific data on identity, health, diet, mobility and kinship. To understand deathways, it employs a second new methodology, funerary taphonomy. Combining osteobiography and taphonomy allows us to connect ancient lives and deaths. Peninsular Italy provides a substantial test sequence typical of much of Europe. For each of three key periods (Neolithic, 6000-4000 BC; Final Neolithic to Early Bronze Age, 4000-1800 BC; Middle Bronze Age to Iron Age, 1800-600 BC), 200+ individuals will be analysed. The results will allow us to evaluate for the first time how inequality affected lives in prehistoric Europe and what role ancestors played in it.
Max ERC Funding
1 943 548 €
Duration
Start date: 2020-10-01, End date: 2024-09-30
Project acronym AngstroCAP
Project Fundamental and Applied Science using Two Dimensional Angstrom-scale capillaries
Researcher (PI) Radha BOYA
Host Institution (HI) THE UNIVERSITY OF MANCHESTER
Country United Kingdom
Call Details Starting Grant (StG), PE3, ERC-2019-STG
Summary I will construct and apply next generation capillary devices as an exciting experimental platform to enable ground-breaking investigation of structure and dynamics of water at the ultimate molecular scale. These devices are in a lab-on-a-chip type configuration with angstrom-scale channels and atomically smooth walls. I am making them by scrupulous assembly tools in a controllable and reproducible fashion and they are extremely stable. Myself and my team will assemble capillaries of a few microns in length, by sandwiching two blocks of layered crystals, e.g., mica, graphite, boron nitride, separated by an atomically thin 2D-crystal spacer. Inside these channels, we will image water condensation along with simultaneous structure analysis by spectroscopy, under in-situ (temperature, pressure) environments. Another key aim of the project is to produce 2D slit-like pores on a large scale by slicing the pre-made 2D capillaries using sharp diamond knives, and explore their applications in size selective separation and biomolecular translocation. This ambitious research program is only possible because of my extensive angstrom-scale fabrication expertise, coupled with world leading fabrication capabilities at the University of Manchester.
Objectives
1: To utilize angstrom-scale capillaries constructed out of two-dimensional (2D) materials as a versatile platform for studying confinement effect on structure and dynamics of water.
2: To construct new types of angstrom-scale 2D-pores from these capillaries for studying size-selective molecular separation, biomolecular sequencing and translocation.
The project will have a lasting impact in understanding what the angstrom-scale confinement offers in terms of active control of molecular transport. Such confinement effects are efficiently utilized in various natural systems (e.g., protein channels) and the results could even aid in designing elementary building blocks of stimuli responsive artificial fluidic circuitry
Summary
I will construct and apply next generation capillary devices as an exciting experimental platform to enable ground-breaking investigation of structure and dynamics of water at the ultimate molecular scale. These devices are in a lab-on-a-chip type configuration with angstrom-scale channels and atomically smooth walls. I am making them by scrupulous assembly tools in a controllable and reproducible fashion and they are extremely stable. Myself and my team will assemble capillaries of a few microns in length, by sandwiching two blocks of layered crystals, e.g., mica, graphite, boron nitride, separated by an atomically thin 2D-crystal spacer. Inside these channels, we will image water condensation along with simultaneous structure analysis by spectroscopy, under in-situ (temperature, pressure) environments. Another key aim of the project is to produce 2D slit-like pores on a large scale by slicing the pre-made 2D capillaries using sharp diamond knives, and explore their applications in size selective separation and biomolecular translocation. This ambitious research program is only possible because of my extensive angstrom-scale fabrication expertise, coupled with world leading fabrication capabilities at the University of Manchester.
Objectives
1: To utilize angstrom-scale capillaries constructed out of two-dimensional (2D) materials as a versatile platform for studying confinement effect on structure and dynamics of water.
2: To construct new types of angstrom-scale 2D-pores from these capillaries for studying size-selective molecular separation, biomolecular sequencing and translocation.
The project will have a lasting impact in understanding what the angstrom-scale confinement offers in terms of active control of molecular transport. Such confinement effects are efficiently utilized in various natural systems (e.g., protein channels) and the results could even aid in designing elementary building blocks of stimuli responsive artificial fluidic circuitry
Max ERC Funding
1 619 466 €
Duration
Start date: 2020-02-01, End date: 2025-01-31
Project acronym ANTSIE
Project ANTarctic Sea Ice Evolution from a novel biological archive
Researcher (PI) Erin Louise MCCLYMONT
Host Institution (HI) UNIVERSITY OF DURHAM
Country United Kingdom
Call Details Consolidator Grant (CoG), PE10, ERC-2019-COG
Summary Antarctic sea ice is a critical component of Earth’s climate system. Seasonal fluctuations support unique ecosystems and impact planetary albedo, ocean-atmosphere exchanges of heat and climatically-active gases (e.g. CO2), and formation of intermediate and deep water masses which create the world’s largest sink of heat and carbon. The properties of the sea-ice pack are complex: despite its climatic significance, Antarctic sea ice is challenging to observe and to model, leading to low confidence in future projections in a warming climate.
The geological record offers a longer-term context for recent trends. At the last glacial maximum (LGM) a likely doubling of Antarctic sea-ice extent relative to today is hypothesised to have driven an ocean drawdown of atmospheric CO2. However, a combination of sparse empirical datasets and uncertainties in sea-ice modelling means that the properties and climatic impacts of the LGM Antarctic sea-ice pack are poorly understood. The narrow focus of the geological record on key primary producers and grazers further limits our understanding of Antarctic ecosystem responses to changes in sea ice.
ANTSIE will exploit a unique biological archive of Antarctic sea-ice conditions to generate a novel ecosystem perspective on the patterns and properties of sea ice during and since the LGM. ‘Antarctic mumiyo’ sequences are preserved remains of regurgitated stomach contents from snow petrels, which feed within and at the edges of the sea-ice pack. A network of mumiyo sequences, which sample across the climatically important Weddell Sea region, will be geochemically analysed to determine snow petrel diet and sea-ice properties with unprecedented century-scale resolution. The results will be used to evaluate new state-of-the-art simulations of the LGM sea-ice pack. By integrating multi-disciplinary perspectives, ANTSIE will provide new understanding of Antarctic sea-ice controls and impacts, to facilitate improved confidence in future project.
Summary
Antarctic sea ice is a critical component of Earth’s climate system. Seasonal fluctuations support unique ecosystems and impact planetary albedo, ocean-atmosphere exchanges of heat and climatically-active gases (e.g. CO2), and formation of intermediate and deep water masses which create the world’s largest sink of heat and carbon. The properties of the sea-ice pack are complex: despite its climatic significance, Antarctic sea ice is challenging to observe and to model, leading to low confidence in future projections in a warming climate.
The geological record offers a longer-term context for recent trends. At the last glacial maximum (LGM) a likely doubling of Antarctic sea-ice extent relative to today is hypothesised to have driven an ocean drawdown of atmospheric CO2. However, a combination of sparse empirical datasets and uncertainties in sea-ice modelling means that the properties and climatic impacts of the LGM Antarctic sea-ice pack are poorly understood. The narrow focus of the geological record on key primary producers and grazers further limits our understanding of Antarctic ecosystem responses to changes in sea ice.
ANTSIE will exploit a unique biological archive of Antarctic sea-ice conditions to generate a novel ecosystem perspective on the patterns and properties of sea ice during and since the LGM. ‘Antarctic mumiyo’ sequences are preserved remains of regurgitated stomach contents from snow petrels, which feed within and at the edges of the sea-ice pack. A network of mumiyo sequences, which sample across the climatically important Weddell Sea region, will be geochemically analysed to determine snow petrel diet and sea-ice properties with unprecedented century-scale resolution. The results will be used to evaluate new state-of-the-art simulations of the LGM sea-ice pack. By integrating multi-disciplinary perspectives, ANTSIE will provide new understanding of Antarctic sea-ice controls and impacts, to facilitate improved confidence in future project.
Max ERC Funding
1 999 929 €
Duration
Start date: 2020-06-01, End date: 2025-11-30
Project acronym Apollo
Project Apollo: developing a powerful and easy to use platform for choice model estimation and application with full user-customisation
Researcher (PI) Stephane HESS
Host Institution (HI) UNIVERSITY OF LEEDS
Country United Kingdom
Call Details Proof of Concept (PoC), ERC-2019-PoC
Summary Mathematical models of human decision making are a widely used tool for advising policy makers and industry by making predictions of future demand for products and services. The reliability of the predictions depends on the robustness of the underlying mathematical models. A very active field of academic research is concerned with the refinement of existing model structures and the development of new approaches. Over the last two decades, fuelled by the availability of ever more powerful computing resources, there has been a major step change in the mathematical complexity of these models. However, the vast majority of real world users of choice models, and also many academic users, lack a programming background. This means that most users are restricted to those models which are covered in existing software, and models developed by analysts who lack programming skills fail to be used in practice.
A core output from the ERC-CoG grant DECISIONS (615596) has been the development of the Apollo package. Apollo is a powerful open source solution for the estimation and application of choice models. The current PoC proposal seeks to fully explore the innovative research that led to the development of Apollo and to take the first steps in establishing Apollo as a next generation tool for choice modelling, with full customisation possibilities including for inexperienced users. We propose to make changes to the existing implementation of Apollo to provide users with an easy to use template for developing code and to create a system for testing user-developed functions for new models, standardise the code used in them, and incorporate them in releases of new versions of Apollo to make them available to other users. In addition, we propose to introduce a pay-to-program service where users can pay to have new features developed. These features will be released to all users after an embargo period during which they are limited to the user who paid for their development.
Summary
Mathematical models of human decision making are a widely used tool for advising policy makers and industry by making predictions of future demand for products and services. The reliability of the predictions depends on the robustness of the underlying mathematical models. A very active field of academic research is concerned with the refinement of existing model structures and the development of new approaches. Over the last two decades, fuelled by the availability of ever more powerful computing resources, there has been a major step change in the mathematical complexity of these models. However, the vast majority of real world users of choice models, and also many academic users, lack a programming background. This means that most users are restricted to those models which are covered in existing software, and models developed by analysts who lack programming skills fail to be used in practice.
A core output from the ERC-CoG grant DECISIONS (615596) has been the development of the Apollo package. Apollo is a powerful open source solution for the estimation and application of choice models. The current PoC proposal seeks to fully explore the innovative research that led to the development of Apollo and to take the first steps in establishing Apollo as a next generation tool for choice modelling, with full customisation possibilities including for inexperienced users. We propose to make changes to the existing implementation of Apollo to provide users with an easy to use template for developing code and to create a system for testing user-developed functions for new models, standardise the code used in them, and incorporate them in releases of new versions of Apollo to make them available to other users. In addition, we propose to introduce a pay-to-program service where users can pay to have new features developed. These features will be released to all users after an embargo period during which they are limited to the user who paid for their development.
Max ERC Funding
150 000 €
Duration
Start date: 2020-02-01, End date: 2022-01-31
