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2. Pushing the frontiers in climate modelling and analysis with machine learning

Author

Eyring, Veronika, Collins, William D., Gentine, Pierre, Barnes, Elizabeth A., Barreiro, Marcelo, Beucler, Tom, Bocquet, Marc, Bretherton, Christopher S., Christensen, Hannah M., Dagon, Katherine, Gagne, David John, Hall, David, Hammerling, Dorit, Hoyer, Stephan, Iglesias-Suarez, Fernando, Lopez-Gomez, Ignacio, McGraw, Marie C., Meehl, Gerald A., Molina, Maria J., Monteleoni, Claire, Mueller, Juliane, Pritchard, Michael S., Rolnick, David, Runge, Jakob, Stier, Philip, Watt-Meyer, Oliver, Weigel, Katja, Yu, Rose, and Zanna, Laure

Published
2024
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6. A Guide to Detracking Math Courses: The Journey to Realize Equity and Access in K-12 Mathematics Education. Corwin Mathematics Series

Author

Torres, Angela, Nguyen, Ho, Barnes, Elizabeth Hull, Wentworth, Laura, Torres, Angela, Nguyen, Ho, Barnes, Elizabeth Hull, and Wentworth, Laura

Abstract

The tracked mathematics system has been operating in US schools for decades. However, research demonstrates negative effects on subgroups of students by keeping them in a single math track, thereby denying them access to rigorous coursework needed for college and career readiness. The journey to change this involves confronting some long-standing beliefs and structures in education. When supported with the right structures, instructional shifts, coalition building, and educator training and support, the detracking of mathematics courses can be a primary pathway to equity. The ultimate goal is to increase more students' access to and achievement in higher levels of mathematics learning--especially for students who are historically marginalized. Based on the stories and lessons learned from the San Francisco Unified School District educators who have talked the talk and walked the walk, this book provides a model for all those involved in taking on detracking efforts from policymakers and school administrators, to math coaches and teachers. By sharing stories of real-world examples, lessons learned, and prompts to provoke discussion about your own context, the book walks you through: (1) Designing and gaining support for a policy of detracked math courses; (2) Implementing the policy through practical shifts in scheduling, curriculum, professional development, and coaching; (3) Supporting and improving the policy through continuous research, monitoring, and maintenance. This book offers the big ideas that help you in your own unique journey to advance equity in your school or district's mathematics education and also provides practical information to help students in a detracked system thrive. [Foreword by Robert Q. Berry III.]

Published
2023

8. Effects of statin therapy on diagnoses of new-onset diabetes and worsening glycaemia in large-scale randomised blinded statin trials: an individual participant data meta-analysis

Author

Reith, Christina, Preiss, David, Blackwell, Lisa, Emberson, Jonathan, Spata, Enti, Davies, Kelly, Halls, Heather, Harper, Charlie, Holland, Lisa, Wilson, Kate, Roddick, Alistair J, Cannon, Christopher P, Clarke, Robert, Colhoun, Helen M, Durrington, Paul N, Goto, Shinya, Hitman, Graham A, Hovingh, G Kees, Jukema, J Wouter, Koenig, Wolfgang, Marschner, Ian, Mihaylova, Borislava, Newman, Connie, Probsfield, Jeffrey L, Ridker, Paul M, Sabatine, Marc S, Sattar, Naveed, Schwartz, Gregory G, Tavazzi, Luigi, Tonkin, Andrew, Trompet, Stella, White, Harvey, Yusuf, Salim, Armitage, Jane, Keech, Anthony, Simes, John, Collins, Rory, Baigent, Colin, Barnes, Elizabeth, Fulcher, Jordan, Herrington, William G, Kirby, Adrienne, O'Connell, Rachel, Amarenco, Pierre, Arashi, Hiroyuki, Barter, Philip, Betteridge, D John, Blazing, Michael, Blauw, Gerard J, Bosch, Jackie, Bowman, Louise, Braunwald, Eugene, Bulbulia, Richard, Byington, Robert, Clearfield, Michael, Cobbe, Stuart, Dahlöf, Björn, Davis, Barry, de Lemos, James, Downs, John R, Fellström, Bengt, Flather, Marcus, Ford, Ian, Franzosi, Maria Grazia, Fuller, John, Furberg, Curt, Glynn, Robert, Goldbourt, Uri, Gordon, David, Gotto, Jr, Antonio, Grimm, Richard, Gupta, Ajay, Hawkins, C Morton, Haynes, Richard, Holdaas, Hallvard, Hopewell, Jemma, Jardine, Alan, Kastelein, John JP, Kean, Sharon, Kearney, Patricia, Kitas, George, Kjekshus, John, Knatterud, Genell, Knopp, Robert H, Koren, Michael, Krane, Vera, Landray, Martin, LaRosa, John, Latini, Roberto, Lonn, Eva, Lucci, Donata, MacFadyen, Jean, Macfarlane, Peter, MacMahon, Stephen, Maggioni, Aldo, Marchioli, Roberto, Moyé, Lemuel, Murphy, Sabina, Neil, Andrew, Nicolis, Enrico B, Packard, Chris, Parish, Sarah, Pedersen, Terje R, Peto, Richard, Pfeffer, Marc, Poulter, Neil, Pressel, Sara, Probstfield, Jeffrey, Rahman, Mahboob, Robertson, Michele, Sacks, Frank, Schmieder, Roland, Serruys, Patrick, Sever, Peter, Shaw, John, Shepherd, James, Simpson, Lara, Sleight, Peter, Smeeth, Liam, Tobert, Jonathan, Tognoni, Gianni, Varigos, John, Wanner, Christoph, Wedel, Hans, Weis, Stephen, Welch, K Michael, Wikstrand, John, Wilhelmsen, Lars, Wiviott, Stephen, Yamaguchi, Junichi, Young, Robin, and Zannad, Faiez

Published
2024
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9. Realistic evacuation simulation through micro and macro scale agent-based modelling including demographics, agent patience and evacuation route capacities

Author

Barnes, Elizabeth May

Abstract

Disasters affect millions of people annually, causing large social impacts, and detrimental economic impacts. Emergency professionals recurrently tackle these impacts, therefore they require assessment methods to understand potential consequences and enable the delivery of resilient resolutions. One method of achieving this is through numerical modelling, specifically agent-based modelling. However, current models simulating human behaviours and movement are bespoke in nature and non-transferable. It has also been found that current modelling tools have either focused on the microscale (e.g. individual confined spaces) or macroscale (e.g. city scale), without considering how the two scales may be interlinked. Further to this, the inclusion of human behaviour has been over-simplified and generic, lacking the inclusion of unique populations with varied characteristics. The aim of this research is to develop a modelling framework, utilising agent-based modelling, to form a more robust representation of human behaviour within an enhanced evacuation model environment. This will allow emergency planners to be better prepared, reduce the interruption after an event (thereby reducing social and economic impacts) and potentially reduce the mitigation required beforehand. The individual agents within the framework capture a range of robust human behaviour indicators (e.g. walking speed, obedience, and patience), allowing the accurate replication of an emergence scenario response. Initially, the research focused on creating a macroscale evacuation model for a test city, to assess whether the inclusion of varied population characteristics and groups of people affected evacuation time. The varied characteristics included a range of ages, gender, and mobility in the form of walking speed. It was then possible to compare this with the parameters of existing evacuation models. This research has found that by enhancing the representation of human behaviour within a model environment more accurate predictions of evacuation time can be produced. To produce more robust human behaviour, models must include a range of population characteristics (such as age, gender and mobility), the grouping of agents and walking speed ratio. When all the variables are included in the model, there is an average increase of 70% in the time to evacuate Newcastle city centre. Even with less variables, i.e. only considering population characteristics, there has been an average increase of 45% in the time to evacuate Newcastle city centre compared with existing models. To further examine human behaviour and the more intricate and detailed behaviours such as patience, a microscale model was created to consider the capacity of the pathways and to introduce congestion. The two microscale models were created of a pavement and a crossroads, ii to replicate people passing and waiting behind slower people, whilst still including the varied population characteristics. When capacity is captured at the microscale, there is an average 61% increase in the time to exit the pavement and when on a crossroads there is an average 87% increase in the time to exit compared to 1.34m/s (3mph) models. Overall, this research has found that there is a need to provide more robust representation of human behaviour characteristics within evacuation models. This must be carried out not only at the macroscale in terms of enhancing population demographics but also at the microscale by capturing intricate behaviours such as taking over and giving way. Without an ability to exhibit these characteristics evacuation simulations cannot effectively capture human behaviour and therefore produce robust simulation times. The inclusion of more representative human behaviour in simulations and the continual need to improve provides the opportunity to reduce the likelihood of increased fatalities and injuries caused by those unable to evacuate in time due to current underestimations. The improvement of computational simulation of evacuations alongside existing simulation techniques allows emergency professionals to plan and prepare better for a range of events to protect global communities.

Published
2022

13. Multi-omic features of oesophageal adenocarcinoma in patients treated with preoperative neoadjuvant therapy

Author

M. Naeini, Marjan, Newell, Felicity, Aoude, Lauren G., Bonazzi, Vanessa F., Patel, Kalpana, Lampe, Guy, Koufariotis, Lambros T., Lakis, Vanessa, Addala, Venkateswar, Kondrashova, Olga, Johnston, Rebecca L., Sharma, Sowmya, Brosda, Sandra, Holmes, Oliver, Leonard, Conrad, Wood, Scott, Xu, Qinying, Thomas, Janine, Walpole, Euan, Tao Mai, G., Ackland, Stephen P., Martin, Jarad, Burge, Matthew, Finch, Robert, Karapetis, Christos S., Shannon, Jenny, Nott, Louise, Bohmer, Robert, Wilson, Kate, Barnes, Elizabeth, Zalcberg, John R., Mark Smithers, B., Simes, John, Price, Timothy, Gebski, Val, Nones, Katia, Watson, David I., Pearson, John V., Barbour, Andrew P., and Waddell, Nicola

Published
2023
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15. Quality of life issues faced by patients with keratinocyte cancer: A systematic review

Author

Kennedy, Samantha K.F., Lee, Shing-Fung, Zhang, Elwyn, Gojsevic, Milena, Rajeswaran, Thenugaa, Chan, Adrian Wai, Wong, Henry C.Y., Sodergren, Samantha, Oren, Dana, Egeler, Mees, Oldenburger, Eva, Young, Teresa, Chalk, Tara, Alchek, Yifat, Barnes, Elizabeth A., Vassiliou, Vassilios, Bonomo, Pierluigi, Mir, Romaana, Hirakawa, Satoshi, Chichel, Adam, Kouloulias, Vassilis, Chow, Edward, and Rembielak, Agata

Published
2024
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20. Phase 2, randomized, double-blind, placebo-controlled multi-center trial of the clinical and biological effects of anti-CD14 treatment in hospitalized patients with COVID-19 pneumonia

Author

Mabrey, F. Linzee, Nian, Hui, Yu, Chang, Barnes, Elizabeth M., Malhotra, Uma, Mikacenic, Carmen, Goldstein, Julia, O'Mahony, D. Shane, Garcia-Diaz, Julia, Finn, Patricia, Voelker, Kirk, Morrell, Eric D., Self, Wesley H., Becker, Patrice M., Martin, Thomas R., and Wurfel, Mark M.

Published
2023
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23. Effect of statin therapy on muscle symptoms: an individual participant data meta-analysis of large-scale, randomised, double-blind trials

Author

Reith, Christina, Baigent, Colin, Blackwell, Lisa, Emberson, Jonathan, Spata, Enti, Davies, Kelly, Halls, Heather, Holland, Lisa, Wilson, Kate, Armitage, Jane, Harper, Charlie, Preiss, David, Roddick, Alistair, Keech, Anthony, Simes, John, Collins, Rory, Barnes, Elizabeth, Fulcher, Jordan, Herrington, William G, Kirby, Adrienne, Mihaylova, Borislava, O'Connell, Rachel, Amarenco, Pierre, Barter, Philip, Betteridge (deceased), D John, Blazing, Michael, Bosch, Jackie, Bowman, Louise, Braunwald, Eugene, Cannon, Christopher P, Clearfield, Michael, Cobbe, Stuart, Colhoun, Helen M, Dahlöf, Björn, Davis, Barry, de Lemos, James, Downs, John R, Durrington, Paul N, Fellström, Bengt, Ford, Ian, Franzosi, Maria Grazia, Fuller (deceased), John, Furberg, Curt, Glynn, Robert, Gordon, David, Gotto Jr, Antonio, Grimm, Richard, Gupta, Ajay, Hawkins, C Morton, Hitman, Graham A, Holdaas (deceased), Hallvard, Jardine, Alan, Jukema, J Wouter, Kastelein, John JP, Kean, Sharon, Kjekshus, John, Knatterud (deceased), Genell, Knopp (deceased), Robert H, Koenig, Wolfgang, Koren, Michael, Krane, Vera, Landray, Martin, LaRosa, John, Latini, Roberto, Lonn, Eva, Lucci, Donata, MacFadyen, Jean, Macfarlane, Peter, MacMahon, Stephen, Maggioni, Aldo, Marchioli, Roberto, Marschner, Ian, Moyé, Lemuel, Murphy, Sabina, Neil, Andrew, Nicolis, Enrico B, Packard, Chris, Parish, Sarah, Pedersen, Terje R, Peto, Richard, Pfeffer, Marc, Poulter, Neil, Pressel, Sara, Probstfield, Jeffrey, Rahman, Mahboob, Ridker, Paul M, Robertson, Michele, Sacks, Frank, Sattar, Naveed, Schmieder, Roland, Serruys, Patrick W, Sever, Peter, Shaw (deceased), John, Shepherd (deceased), James, Simpson, Lara, Sleight (deceased), Peter, Tavazzi, Luigi, Tognoni, Gianni, Tonkin, Andrew, Trompet, Stella, Wanner, Christoph, Wedel, Hans, Weis, Stephen, Welch, K Michael, White, Harvey, Wikstrand, John, Wilhelmsen, Lars, Wiviott, Stephen, Young, Robin, Yusuf, Salim, Zannad, Faiez, Arashi, Hiroyuki, Byington, Robert, Clarke, Robert, Flather, Marcus, Goldbourt, Uri, Goto, Shinya, Hopewell, Jemma, Hovingh, Kees, Kearney, Patricia, Kitas, George, Newman, Connie, Sabatine, Marc S, Schwartz, Greg, Smeeth, Liam, Tobert, Jonathan, Varigos, John, and Yamaguchi, Junichi

Published
2022
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25. Data‐Driven Predictions of Peak Warming Under Rapid Decarbonization.

Author

Diffenbaugh, Noah S. and Barnes, Elizabeth A.

Subjects
*CLIMATE change models, *GLOBAL warming, *CARBON emissions, *CONVOLUTIONAL neural networks, PARIS Agreement (2016)
Abstract

The severe impacts associated with recent record‐setting annual global temperatures elevate the need to accurately predict the hottest conditions that could occur even if the most ambitious decarbonization goals are achieved. We use convolutional neural networks (CNNs) to predict peak global warming from recent observed temperature maps and future cumulative CO2 emissions. For the SSP1‐1.9 decarbonization scenario there is >99% probability that mean global warming exceeds 1.5°C, approximately even odds that it reaches 2°C, and ∼90% probability that the hottest year globally exceeds 2023 by at least 0.5°C. Further, for the SSP2‐4.5 decarbonization scenario, there is >90% probability that the hottest annual global temperature anomaly is twice the 2023 anomaly. That our framework makes highly accurate out‐of‐sample predictions of the hottest historical year provides confidence in the predicted future probabilities, suggesting substantial risks from the extreme local conditions that are likely to result from globally hot years during rapid decarbonization. Plain Language Summary: Calendar year 2023 was the hottest year on record globally, reaching ∼1.5°C above the pre‐industrial. Many national, sub‐national and non‐state actors have articulated ambitious decarbonization goals to stabilize the global temperature. However, the intensifying impacts as individual years have approached 1.5°C have heightened the need to more accurately predict not just the mean warming but also the hottest years that could occur even in the context of rapid decarbonization. We train neural networks on an ensemble of global climate models and then use historical observations as input to the trained networks, thus constraining the uncertainty in climate model projections by using the current state of the climate system as the basis for a truly out‐of‐sample prediction. For the historical period, we find that, despite a wide range of climate sensitivities across global climate models, the neural networks make highly accurate predictions of the hottest historical year when given observed climate patterns as out‐of‐sample inputs. Predicting future warming under different cumulative emissions, we find that even if net‐zero emissions are achieved mid‐century, mean warming is virtually certain to exceed 1.5°C and has even odds of reaching 2°C, with high likelihood of individual years that are at least 0.5°C hotter than 2023. Key Points: We train CNNs to predict peak global warming given the map of recent annual temperatures and total additional CO2 emissionsEven if net‐zero emissions are reached mid‐century, mean warming is virtually certain to exceed 1.5°C, with even odds of 2°CThere is high likelihood of individual years that are at least 0.5°C hotter than 2023 even in the most ambitious decarbonization scenario [ABSTRACT FROM AUTHOR]

Published
2024
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27. A study of the effects of home administered transcutaneous electrical nerve stimulation on quality of life, psychosocial and incontinence outcomes in children with overactive bladder syndrome.

Author

Hamilton, Sana, Deshpande, Aniruddh, Nankivell, Gail, Barnes, Elizabeth H, and Caldwell, Patrina

Abstract

Main problem There is uncertainty about the effect of transcutaneous electrical nerve stimulation on quality of life and psychosocial outcomes in children with lower urinary tract symptoms. We aim to describe its impact on quality of life, psychosocial outcomes and lower urinary tract symptoms in Australian children with overactive bladder while exploring the role of confounders including baseline co-morbidities and length of transcutaneous electrical nerve stimulation usage at home. Methods Children aged four to 18 years with symptoms of overactive bladder were given a transcutaneous electrical nerve stimulation machine for use at home. Data was collected at baseline and again three months later using a modified Paediatric Incontinence Quality of life Questionnaire, Strengths and Difficulties Questionnaire and an Incontinence Questionnaire and compared using paired t-tests. Separate analysis by gender, lower urinary tract symptoms and comorbidities was conducted. Results Thirty-one children (15 girls) aged six to 16 years enrolled. The mean change in total Quality of Life Questionnaire score from baseline to post-treatment was -0.2 (95%CI-0.5 to 0.1; p=0.1), change in total Strengths and Difficulty Questionnaire score was -0.1 (95%CI-1.5 to 1.2; p=0.8) and change in total Incontinence Questionnaire score was -1.9 (95%CI-2.9 to -1.0; p=0.0004). Five participants who were positive for lower urinary tract symptoms at baseline became negative post treatment, whereas no participants without symptoms at baseline became positive post-treatment (p=0.025). Conclusions Transcutaneous electrical nerve stimulation monotherapy administered at home is potentially an effective treatment option for children with overactive bladder without adversely affecting their quality of life and psychosocial wellbeing. [ABSTRACT FROM AUTHOR]

Published
2024
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33. Forecasts of Opportunity : Opening Windows of Skill, Subseasonal and Beyond

Author

Mariotti, Annarita, Baggett, Cory, Barnes, Elizabeth A., Becker, Emily, Butler, Amy, Collins, Dan C., Dirmeyer, Paul A., Ferranti, Laura, Johnson, Nathaniel C., Jones, Jeanine, Kirtman, Ben P., Lang, Andrea L., Molod, Andrea, Newman, Matthew, Robertson, Andrew W., Schubert, Siegfried, Waliser, Duane E., and Albers, John

Published
2020

34. Windows of Opportunity for Skillful Forecasts Subseasonal to Seasonal and Beyond

Author

Mariotti, Annarita, Baggett, Cory, Barnes, Elizabeth A., Becker, Emily, Butler, Amy, Collins, Dan C., Dirmeyer, Paul A., Ferranti, Laura, Johnson, Nathaniel C., Jones, Jeanine, Kirtman, Ben P., Lang, Andrea L., Molod, Andrea, Newman, Matthew, Robertson, Andrew W., Schubert, Siegfried, Waliser, Duane E., and Albers, John

Published
2020

38. Maternal autoimmunity and inflammation are associated with childhood tics and obsessive-compulsive disorder: Transcriptomic data show common enriched innate immune pathways

Author

Jones, Hannah F., Han, Velda X., Patel, Shrujna, Gloss, Brian S., Soler, Nicolette, Ho, Alvin, Sharma, Suvasini, Kothur, Kavitha, Nosadini, Margherita, Wienholt, Louise, Hardwick, Chris, Barnes, Elizabeth H., Lim, Jacqueline R., Alshammery, Sarah, Nielsen, Timothy C., Wong, Melanie, Hofer, Markus J., Nassar, Natasha, Gold, Wendy, Brilot, Fabienne, Mohammad, Shekeeb S., and Dale, Russell C.

Published
2021
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41. Reply to commentaries on <italic>Health Problems</italic>.

Author

Barnes, Elizabeth

Subjects
*WELL-being, *DISABILITIES, *CONFERENCES & conventions, *HOPE, *AUTHORS
Abstract

I am grateful to and honored by the time the authors in this symposium have taken to discuss my recent book Health Problems. I don’t have the space in what follows to fully address the issues they raise, but I hope to highlight some key points of challenge and disagreement, and offer some preliminary responses. [ABSTRACT FROM AUTHOR]

Published
2024
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42. Healthy skepticism: A <italic>précis</italic> of Health Problems.

Author

Barnes, Elizabeth

Subjects
*CORONARY artery disease, *CARDIOVASCULAR system, *ARTERIAL diseases, *MEDICAL care research, *TAKOTSUBO cardiomyopathy
Abstract

The article "Healthy skepticism: A précis of health problems" by Elizabeth Barnes explores the philosophical complexities surrounding the concept of health. Barnes argues that health is not only biologically important but also has normative, political, and phenomenological significance. The article delves into the challenges of defining health, the interplay between health and well-being, and proposes the concept of ameliorative skepticism as a way to navigate the inherent tensions in understanding health. Overall, the article highlights the need for better philosophical methodologies to address complex questions about health that may not have definitive answers. [Extracted from the article]

Published
2024
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43. Projected changes to Arctic shipping routes after stratospheric aerosol deployment in the ARISE-SAI scenarios.

Author

Morrison, Ariel L., Pathak, Debanjali, Barnes, Elizabeth A., and Hurrell, James W.

Subjects
SEA ice, CLIMATE change, OCEAN temperature, AEROSOLS
Abstract

Introduction: Rapid reductions in Arctic sea ice in response to warming have led to increased interest in using the Arctic Ocean for commercial shipping. As the world warms, however, different strategies are being considered to stabilize or reduce surface temperatures in order to prevent critical climate change impacts. One such strategy is stratospheric aerosol injection (SAI), a form of solar climate intervention. Projected changes to Arctic sea ice under SAI with specific regards to shipping have not yet been assessed. Methods: We compare output from two SAI simulations that have different global mean temperature targets with a non-SAI control simulation to provide the first assessment of Arctic Ocean navigability under potential SAI scenarios. Results: We find that sea ice concentration and thickness quickly stabilize or increase after SAI deployment. When sea ice thickness stabilizes in response to SAI, the number of days when the Arctic Ocean is navigable remains fairly constant, but increasing sea ice thickness leads to reduced navigability compared to the non-SAI simulation. From 2035-2069, both the Northwest Passage and Northern Sea Route are accessible from July-November in all three simulations, but there are no navigable routes under either SAI scenario from April-June. When the Arctic is navigable, it can take 2-12 days longer to cross the Arctic Ocean in the SAI simulations than in the non-SAI control simulation, and there are large year-to-year variations in travel time. Discussion: Overall, Arctic shipping may take longer and be more difficult in an SAI vs a non-SAI world because of relatively thicker sea ice, but the degree to which Arctic shipping may change in response to SAI is dependent on the particular climate intervention strategy. [ABSTRACT FROM AUTHOR]

Published
2024
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44. Machine learning-based extreme event attribution.

Author

Trok, Jared T., Barnes, Elizabeth A., Davenport, Frances V., and Diffenbaugh, Noah S.

Subjects
*HEAT waves (Meteorology), *EXTREME weather, *CONVOLUTIONAL neural networks, *SEASONAL temperature variations, *GLOBAL warming
Abstract

The observed increase in extreme weather has prompted recent methodological advances in extreme event attribution. We propose a machine learning-based approach that uses convolutional neural networks to create dynamically consistent counterfactual versions of historical extreme events under different levels of global mean temperature (GMT). We apply this technique to one recent extreme heat event (southcentral North America 2023) and several historical events that have been previously analyzed using established attribution methods. We estimate that temperatures during the southcentral North America event were 1.18° to 1.42°C warmer because of global warming and that similar events will occur 0.14 to 0.60 times per year at 2.0°C above preindustrial levels of GMT. Additionally, we find that the learned relationships between daily temperature and GMT are influenced by the seasonality of the forced temperature response and the daily meteorological conditions. Our results broadly agree with other attribution techniques, suggesting that machine learning can be used to perform rapid, low-cost attribution of extreme events. [ABSTRACT FROM AUTHOR]

Published
2024
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