̽��ֱ�� of Cambridge - ̽��ֱ�� of Newcastle

Ice sheets can collapse faster than previously thought possible

sc604 — Wed, 05 Apr 2023 14:59:35 +0000

An international team of researchers used high-resolution imagery of the seafloor to reveal just how quickly a former ice sheet that extended from Norway retreated at the end of the last Ice Age, about 20,000 years ago.

̽��ֱ��team, including researchers from the ̽��ֱ�� of Cambridge, mapped more than 7,600 small-scale landforms called corrugation ridges across the seafloor. ̽��ֱ��ridges are less than 2.5 metres high and are spaced between about 25 and 300 metres apart.

These landforms are understood to have formed when the ice sheet’s retreating margin moved up and down with the tides, pushing seafloor sediments into a ridge every low tide. Given that two ridges would have been produced each day, the researchers were able to calculate how quickly the ice sheet retreated.

Their results, reported in the journal Nature, show the former ice sheet underwent pulses of rapid retreat at a speed of 50 to 600 metres per day. This is much faster than any ice sheet retreat rate that has been observed from satellites or inferred from similar landforms in Antarctica.

“Our research provides a warning from the past about the speeds that ice sheets are physically capable of retreating at,” said Dr Christine Batchelor from Newcastle ̽��ֱ��, who led the research. “Our results show that pulses of rapid retreat can be far quicker than anything we’ve seen so far.”

Information about how ice sheets behaved during past periods of climate warming is important to inform computer simulations that predict future ice sheet and sea-level change.

“This study shows the value of acquiring high-resolution imagery about the glaciated landscapes that are preserved on the seafloor,” said co-author Dr Dag Ottesen from the Geological Survey of Norway, who is involved in the MAREANO seafloor mapping programme that collected the data.

̽��ֱ��new research suggests that periods of such rapid ice-sheet retreat may only last for short periods of time: from days to months.

“This shows how rates of ice-sheet retreat averaged over several years or longer can conceal shorter episodes of more rapid retreat,” said co-author Professor Julian Dowdeswell from Cambridge’s Scott Polar Research Institute. “It is important that computer simulations are able to reproduce this ‘pulsed’ ice-sheet behaviour.”

̽��ֱ��seafloor landforms also shed light into the mechanism by which such rapid retreat can occur. ̽��ֱ��researchers found that the former ice sheet had retreated fastest across the flattest parts of its bed.

“An ice margin can unground from the seafloor and retreat near-instantly when it becomes buoyant,” said co-author Dr Frazer Christie, also from the Scott Polar Research Institute. “This style of retreat only occurs across relatively flat beds, where less melting is required to thin the overlying ice to the point where it starts to float.”

̽��ֱ��researchers conclude that pulses of similarly rapid retreat could soon be observed in parts of Antarctica. This includes at West Antarctica’s vast Thwaites Glacier, which is the subject of considerable international research due to its potential susceptibility to unstable retreat. ̽��ֱ��authors of this new study suggest that Thwaites Glacier could undergo a pulse of rapid retreat because it has recently retreated close to a flat area of its bed.

“Our findings suggest that present-day rates of melting are sufficient to cause short pulses of rapid retreat across flat-bedded areas of the Antarctic Ice Sheet, including at Thwaites”, said Batchelor. “Satellites may well detect this style of ice-sheet retreat in the near future, especially if we continue our current trend of climate warming.”

Other co-authors are Dr Aleksandr Montelli and Evelyn Dowdeswell at the Scott Polar Research Institute, Dr Jeffrey Evans at Loughborough ̽��ֱ��, and Dr Lilja Bjarnadóttir at the Geological Survey of Norway. ̽��ֱ��study was supported by Peterhouse, Cambridge, the Faculty of Humanities and Social Sciences at Newcastle ̽��ֱ��, the Prince Albert II of Monaco Foundation, and the Geological Survey of Norway.

Reference:
Christine L Batchelor et al. ‘Rapid, buoyancy-driven ice-sheet retreat of hundreds of metres per day’. Nature (2023), DOI: 10.1038/s41586-023-05876-1

Adapted from a press release by Newcastle ̽��ֱ��.

Ice sheets can retreat up to 600 metres a day during periods of climate warming, 20 times faster than the highest rate of retreat previously measured.

Copernicus EU/ESA, processed by Dr Frazer Christie

Sentinel-1 image composite depicting the highly fractured and fast-flowing frontal margin of the Thwaites and Crosson ice shelves

̽��ֱ��text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

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̽��ֱ��off-patent drug that could protect us from future COVID-19 variants

cjb250 — Mon, 05 Dec 2022 16:00:00 +0000

Cambridge scientists have identified a drug that can be repurposed to prevent COVID-19 in research involving a unique mix of ‘mini-organs’, donor organs, animal studies and patients.

Experts urge government to keep focus on levelling-up health

cjb250 — Fri, 30 Sep 2022 10:32:46 +0000

Writing in Public Health in Practice and based on a review of all the previous literature, the team sets out a five-point framework to help level-up health and tackle health inequalities, which they say have been exacerbated by the COVID-19 pandemic.

̽��ֱ��UK Government committed to a programme of ‘levelling-up’ to help left-behind areas and regions to recover and prosper to the same extent as other parts of the country, including a £4.8 billion Levelling Up Fund. With the departure of Boris Johnson as Prime Minister, the researchers urge the new Government to reaffirm their commitment to levelling up.

With the fallout from the pandemic and rise in the cost of living, the impact on health is expected to be substantial due to the long-term economic repercussions of the pandemic, including food and housing insecurity, debt, and poverty.

Dr John Ford from Cambridge Public Health at the ̽��ֱ�� of Cambridge said: “It feels like we’re at a pivotal point as the Government moves its focus away from levelling-up and towards economic growth. It’s crucial that they consider closing the health gap – which has only got worse during the pandemic – as an urgent priority.

“This will not be straightforward to achieve and will require cross-government – and cross-party – support and long-term planning. That’s why we’re setting out five evidence-based principles that will help ensure the success of any health levelling-up programmes.”

Dr Ford and colleagues carried out a review of the research literature to develop a practical, evidence-based framework to level up health that can be implemented across sectors, including governments or non-profits, and across a diversity of scales, from local to national, and a diversity of contexts.

̽��ֱ��five overlapping principles identified by the group are:

Make interventions healthy by default and easy to use – In other words, make healthy choices easier to make. Past examples that have proven successful include: taxing unhealthy foods and subsidising healthy foods was consistently documented as an intervention type; providing fluoride toothpaste for home use and daily toothbrushing supervision for 5-year-olds.
Focus on long-term solutions working across many sectors – For example, while tackling housing conditions may be important, this alone is unlikely to be effective when individuals are still impacted by other factors such as working conditions or access to healthy foods: housing interventions are more likely to be effective in improving health and reducing inequalities when there were multiple interventions targeting several social determinants of health.
Tailor initiatives at a local level – For example, flu vaccination programmes are likely to be more successful if they can be offered outside of traditional working hours, while including community-based infrastructure developments in physical activity interventions can make them more sustainable, maintain increased adult physical activity levels and reduce inequalities.
Target disadvantaged communities – Universally-applied programmes that do not also target disadvantaged communities or account for their particular needs, assets, and barriers to health are less effective in reducing health inequalities and may even widen them. Provision of benefits to disadvantaged groups may also reduce health inequalities, such as food subsidy programmes for women of low-socioeconomic status that aim to reduce inequalities in mean birth weight and food/nutrient uptake.
Allocate resources according to need – Studies have shown that allocating resources where they are most needed – for example, the allocation of NHS resources proportionate to geographic need, with more deprived areas receiving more resources – is most effective at reducing inequalities.

Professor Clare Bambra from Newcastle ̽��ֱ�� said: “Health inequalities have arisen over decades, if not centuries, but underlying them is often the same root cause: an unequal distribution of the wider determinants of health, such as access to resources, opportunities, wealth, education, and power.

“There is no silver bullet that will solve this problem. If we are serious about tacking this problem, then we’ll need a holistic approach, with long-term, collaborative and cross-government strategies that look beyond just one election cycle.”

̽��ֱ��research was commissioned by Public Health England and undertaken in collaboration with Newcastle ̽��ֱ��.

Reference
Davey, F et al. Levelling up health: A practical, evidence-based framework for reducing health inequalities. Public Health in Practice; 30 Sept 2022; DOI: 10.1016/j.puhip.2022.100322

Experts are calling on the Government to continue focusing on ‘levelling-up’ health, arguing that reducing the health gap is too important an agenda to abandon.

It’s crucial that the government considers closing the health gap – which has only got worse during the pandemic – as an urgent priority

John Ford

Richard Johnson (Getty Images)

High-rise council flats in housing estate in Port Glasgow, Inverclyde

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

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Sea ice can control Antarctic ice sheet stability, new research finds

sc604 — Fri, 13 May 2022 09:00:50 +0000

Despite the rapid melting of ice in many parts of Antarctica during the second half of the 20th century, researchers have found that the floating ice shelves which skirt the eastern Antarctic Peninsula have undergone sustained advance over the past 20 years.

AI techniques used to improve battery health and safety

sc604 — Mon, 06 Apr 2020 10:58:14 +0000

̽��ֱ��researchers, from Cambridge and Newcastle Universities, have designed a new way to monitor batteries by sending electrical pulses into them and measuring the response. ̽��ֱ��measurements are then processed by a machine learning algorithm to predict the battery’s health and useful lifespan. Their method is non-invasive and is a simple add-on to any existing battery system. ̽��ֱ��results are reported in the journal Nature Communications.

Predicting the state of health and the remaining useful lifespan of lithium-ion batteries is one of the big problems limiting widespread adoption of electric vehicles: it’s also a familiar annoyance to mobile phone users. Over time, battery performance degrades via a complex network of subtle chemical processes. Individually, each of these processes doesn’t have much of an effect on battery performance, but collectively they can severely shorten a battery’s performance and lifespan.

Current methods for predicting battery health are based on tracking the current and voltage during battery charging and discharging. This misses important features that indicate battery health. Tracking the many processes that are happening within the battery requires new ways of probing batteries in action, as well as new algorithms that can detect subtle signals as they are charged and discharged.

"Safety and reliability are the most important design criteria as we develop batteries that can pack a lot of energy in a small space," said Dr Alpha Lee from Cambridge’s Cavendish Laboratory, who co-led the research. "By improving the software that monitors charging and discharging, and using data-driven software to control the charging process, I believe we can power a big improvement in battery performance."

̽��ֱ��researchers designed a way to monitor batteries by sending electrical pulses into it and measuring its response. A machine learning model is then used to discover specific features in the electrical response that are the tell-tale sign of battery aging. ̽��ֱ��researchers performed over 20,000 experimental measurements to train the model, the largest dataset of its kind. Importantly, the model learns how to distinguish important signals from irrelevant noise. Their method is non-invasive and is a simple add-on to any existing battery systems.

̽��ֱ��researchers also showed that the machine learning model can be interpreted to give hints about the physical mechanism of degradation. ̽��ֱ��model can inform which electrical signals are most correlated with aging, which in turn allows them to design specific experiments to probe why and how batteries degrade.

"Machine learning complements and augments physical understanding," said co-first author Dr Yunwei Zhang, also from the Cavendish Laboratory. " ̽��ֱ��interpretable signals identified by our machine learning model are a starting point for future theoretical and experimental studies."

̽��ֱ��researchers are now using their machine learning platform to understand degradation in different battery chemistries. They are also developing optimal battery charging protocols, powering by machine learning, to enable fast charging and minimise degradation.

This work was carried out with funding from the Faraday Institution. Dr Lee is also a Research Fellow at St Catharine’s College.

Reference:
Yunwei Zhang et al. ‘Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning.’ Nature Communications (2020). DOI: 10.1038/s41467-020-15235-7

Researchers have designed a machine learning method that can predict battery health with 10x higher accuracy than current industry standard, which could aid in the development of safer and more reliable batteries for electric vehicles and consumer electronics.

Nordwood Themes via Unsplash

Person holding white Android phone

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New initiative to train specialists in risk, mitigation and Big Data

sc604 — Tue, 03 Feb 2015 18:00:01 +0000

Hosted as a Centre for Doctoral Training (CDT) and funded by the Natural Environment Research Council (NERC), the aim of the consortium is to produce a cohort of researchers who can use large or complex datasets to understand and ease the risks posed by a range of societal and environmental changes, such as a rapidly expanding population, limited natural resources, and natural hazards.

It’s imperative that business, government and wider society understand these risks so that they can develop appropriate mitigation strategies. Many businesses already recognise the need to understand and reduce the risks to infrastructure, operations and supply chains.

Through the insurance and reinsurance industries, for example, the UK is a world-renowned international centre in risk assessment, modelling and its application. ̽��ֱ��sector values strong collaboration with the UK academic research base to enable the improvement of their risk models, maintain a competitive edge, and grow their markets. As a result, the UK insurance sector is the largest in Europe, making a major contribution to the UK economy, employing 320,000 people and contributing almost 3% to GDP.

But other industries and humanitarian and development organisations also need the tools to help them assess the risks arising from increasingly complex and interconnected hazards, for example, international disaster risk reduction.

And, as identified by the recent BIS data strategy – Seizing the Data Opportunity – the UK has some of the best universities and institutes in the world, some truly innovative small businesses, and some of the richest historic datasets of any country.

This means there’s potential to produce a new generation of risk scientists able to maximise the opportunities big data offers, filling a skills shortage in this area. ̽��ֱ��CDT is a direct response to this shortage.

Minister for Universities, Science & Cities, Greg Clark, said: “In this fast-moving, digital world, the ability to handle and analyse large volumes of complex data is vital for the UK to maintain its competitive edge. That is why the government identified Big Data as one of our 8 Great Technologies and central to our Industrial Strategy.

“This £2.5 million investment to train the next generation of Big Data experts will enable a skilled workforce to develop innovative tools to assess and mitigate risk that will help business, government and wider society cope effectively with big environmental and societal changes.”

Professor Simon Pollard of Cranfield ̽��ֱ�� will lead the consortium, called DREAM (Data, Risk and Environmental Analytical Methods). It will include researchers from the ̽��ֱ�� of Cambridge, Newcastle ̽��ֱ�� and the ̽��ֱ�� of Birmingham, together with a wide range of partners from the private and public sectors. Dr Mike Bithell from Cambridge’s Department of Geography is one of four centre directors for the programme.

Funding for ten studentships will be awarded each year. ̽��ֱ��CDT award will provide funding for three years of new student intake – 30 studentships in total – from 2015 to 2016. Two of the studentships in the 2016 cohort will be interdisciplinary and co-funded by the Economic and Social Research Council (ESRC) and NERC.

Students will gain advanced technical skills, be regularly brought together as a cohort to share ideas and skills, and have the opportunity to take part in partner-based secondments.

CDTs support strategically-targeted, focused PhD studentships aimed at addressing specific research and skills gaps.

Cambridge is one of four leading UK universities awarded funding to train the next generation of researchers to become experts at assessing and mitigating risk using Big Data.

In this fast-moving, digital world, the ability to handle and analyse large volumes of complex data is vital for the UK to maintain its competitive edge

Greg Clark

kris krüg

2013 Esri International User Conference

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From Mexican wave to retinal wave: why sharing data is good for science

jfp40 — Mon, 07 Apr 2014 10:40:34 +0000

Now, researchers at Cambridge, York, Newcastle and Imperial College London have developed a system allowing neurophysiologists to share raw data with each other, something they hope will generate new discoveries in the field. ̽��ֱ��results are published in the journal GigaScience.

̽��ֱ��first type of data they collected and standardised are recordings of so called ‘retinal waves’. During early development, retinal neurons generate signals that rapidly spread across from one cell to another, much like a Mexican wave in a football stadium. These patterns of activity are thought to help forge the neural connections from the eye to the brain.

To record retinal waves, scientists use multielectrode arrays (tiny electrical devices). In this research, the team took 366 recordings from 12 different studies published between 1993 and 2014, converted them all to HDF5 – a standard open source format – and published them in a web-based ‘virtual laboratory’ called CARMEN.

According to lead author Dr Stephen Eglen from the Cambridge Computational Biology Institute: “Unlike other fields such as genomics, there hasn’t been much public data sharing in neuroscience, which could be because the data are heterogeneous and hard to annotate, or because researchers are reluctant to share data with a competitor.”

But Eglen believes there is much to be gained by a more cooperative approach. “There are two main benefits to sharing,” he said. “As well as leading to other collaborations and more interesting research, it also means that other people can check what you’ve done, which leads to more robust research. And if the taxpayer funds research, then I think it’s important for those results to be publicly available.”

CARMEN was a pilot project funded by the EPSRC, and is now supported by the BBSRC.

From the way we learn, to how our memories are made and stored, the workings of our brains depend on connections forged between billions of neurons, yet much about how our nervous system develops remains a mystery.

There are two main benefits to sharing. As well as leading to other collaborations and more interesting research, it also means that other people can check what you’ve done, which leads to more robust research.

Dr Stephen Eglen

Oyvind Solstad

Eye 9

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