Pub Date : 2024-12-05DOI: 10.1038/s44304-024-00040-9
Kristen M. Joyse, Michael L. Stein, Benjamin P. Horton, Robert E. Kopp
Estimates of extreme sea-level return periods guide flood hazard mitigation. Return period estimates calculated from tide gauge records, which are relatively short (typically less than 100 years), can fail to capture the rarest and most potentially impactful extreme events. Here, we employ a two-dimensional Poisson point process model to fuse water-level data from tide gauges with data from multi-century geologic records of extreme overwash events. Experiments with synthetic data show that including geologic data reduces the uncertainty of 1% and 0.1% average annual chance water levels by about half, relative to using tide gauge data alone. Similar uncertainty reductions occur with two case studies of geologic data (Mattapoisett Marsh, Massachusetts and Cheesequake, New Jersey) and their neighboring tide gauges (Woods Hole, Massachusetts and the Battery, New York). The analysis also reveals non-stationarity at Cheesequake and The Battery, arising from either climatic changes or changes in the fidelity of the geological record, with substantially higher 1–10% average annual chance water levels since 1900 compared to prior centuries.
{"title":"Multi-century geological data thins the tail of observationally based extreme sea level return period curves","authors":"Kristen M. Joyse, Michael L. Stein, Benjamin P. Horton, Robert E. Kopp","doi":"10.1038/s44304-024-00040-9","DOIUrl":"10.1038/s44304-024-00040-9","url":null,"abstract":"Estimates of extreme sea-level return periods guide flood hazard mitigation. Return period estimates calculated from tide gauge records, which are relatively short (typically less than 100 years), can fail to capture the rarest and most potentially impactful extreme events. Here, we employ a two-dimensional Poisson point process model to fuse water-level data from tide gauges with data from multi-century geologic records of extreme overwash events. Experiments with synthetic data show that including geologic data reduces the uncertainty of 1% and 0.1% average annual chance water levels by about half, relative to using tide gauge data alone. Similar uncertainty reductions occur with two case studies of geologic data (Mattapoisett Marsh, Massachusetts and Cheesequake, New Jersey) and their neighboring tide gauges (Woods Hole, Massachusetts and the Battery, New York). The analysis also reveals non-stationarity at Cheesequake and The Battery, arising from either climatic changes or changes in the fidelity of the geological record, with substantially higher 1–10% average annual chance water levels since 1900 compared to prior centuries.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00040-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142778660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-04DOI: 10.1038/s44304-024-00035-6
Carolyn Kousky, Xuesong You
To protect households and communities from growing losses due to natural disasters and stabilize climate-stressed insurance markets, investments in cost-effective risk reduction must be expanded. Using a unique survey of survivors of one of four U.S. landfalling hurricanes, we investigate the decision to invest in mitigation measures during rebuilding. We find that insurers play a key role in this process by providing both information and financial incentives.
{"title":"The role of insurers in driving post-hurricane risk reduction investments","authors":"Carolyn Kousky, Xuesong You","doi":"10.1038/s44304-024-00035-6","DOIUrl":"10.1038/s44304-024-00035-6","url":null,"abstract":"To protect households and communities from growing losses due to natural disasters and stabilize climate-stressed insurance markets, investments in cost-effective risk reduction must be expanded. Using a unique survey of survivors of one of four U.S. landfalling hurricanes, we investigate the decision to invest in mitigation measures during rebuilding. We find that insurers play a key role in this process by providing both information and financial incentives.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00035-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142762922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-04DOI: 10.1038/s44304-024-00039-2
Constance Ting Chua, Takuro Otake, Tanghua Li, An-Chi Cheng, Qiang Qiu, Linlin Li, Anawat Suppasri, Fumihiko Imamura, Adam D. Switzer
Seaports are vulnerable to extreme sea level events. Beyond physical damage, any port inoperability affects trade flows in and out of the affected port and disrupts shipping routes connected to it, which then propagates throughout the port network. Here, we propose an approach to assessing tsunami risk to ports and the global port network. We leverage on the topological properties of the global liner shipping network and centrality measures to quantify the potential impacts of a Manila Trench earthquake-tsunami under both present and future sea levels. We find that a Manila Trench tsunami could potentially damage up to 11 ports at present-day conditions and 15 ports under rising sea levels. Port closure could exceed 200 days and cause greater disruption to shipping routes than historical tsunami events. We also find that sea level rise is likely to result in uneven changes in tsunami heights spatially and hence, uneven impacts on the global port network.
{"title":"An approach to assessing tsunami risk to the global port network under rising sea levels","authors":"Constance Ting Chua, Takuro Otake, Tanghua Li, An-Chi Cheng, Qiang Qiu, Linlin Li, Anawat Suppasri, Fumihiko Imamura, Adam D. Switzer","doi":"10.1038/s44304-024-00039-2","DOIUrl":"10.1038/s44304-024-00039-2","url":null,"abstract":"Seaports are vulnerable to extreme sea level events. Beyond physical damage, any port inoperability affects trade flows in and out of the affected port and disrupts shipping routes connected to it, which then propagates throughout the port network. Here, we propose an approach to assessing tsunami risk to ports and the global port network. We leverage on the topological properties of the global liner shipping network and centrality measures to quantify the potential impacts of a Manila Trench earthquake-tsunami under both present and future sea levels. We find that a Manila Trench tsunami could potentially damage up to 11 ports at present-day conditions and 15 ports under rising sea levels. Port closure could exceed 200 days and cause greater disruption to shipping routes than historical tsunami events. We also find that sea level rise is likely to result in uneven changes in tsunami heights spatially and hence, uneven impacts on the global port network.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-13"},"PeriodicalIF":0.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00039-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142762898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-04DOI: 10.1038/s44304-024-00037-4
Yilong Li, Zhenguo Zhang, Xiaofei Chen
Earthquakes remain unpredictable and pose significant challenges to disaster preparedness. This study develops a rapid assessment framework for earthquake disaster losses based on physical simulations, demonstrated through analysis of the 2021 Ms 6.4 Yangbi earthquake. A finite fault source based on observed data is employed on a GPU-accelerated 3D strong ground motion simulation platform. The computational process considers the effects of 3D heterogeneous velocity structure and terrain. Subsequently, this data is incorporated into a mathematical model for earthquake disaster loss assessment derived from historical statistics, evaluating emergency response levels, fatalities, and economic losses. The inclusion of teleseismic data into this framework underscores its extensive applicability for rapid loss assessments, even in regions lacking local seismic data. Through comparisons with station observation waveforms and government-reported loss, the validity and practicality of the framework were substantiated. It plays a vital role in assisting emergency decisions, optimizing resource allocation, and further mitigating losses.
{"title":"Developing a rapid assessment framework for China earthquake disaster losses: insights from physical simulations of the Yangbi earthquake","authors":"Yilong Li, Zhenguo Zhang, Xiaofei Chen","doi":"10.1038/s44304-024-00037-4","DOIUrl":"10.1038/s44304-024-00037-4","url":null,"abstract":"Earthquakes remain unpredictable and pose significant challenges to disaster preparedness. This study develops a rapid assessment framework for earthquake disaster losses based on physical simulations, demonstrated through analysis of the 2021 Ms 6.4 Yangbi earthquake. A finite fault source based on observed data is employed on a GPU-accelerated 3D strong ground motion simulation platform. The computational process considers the effects of 3D heterogeneous velocity structure and terrain. Subsequently, this data is incorporated into a mathematical model for earthquake disaster loss assessment derived from historical statistics, evaluating emergency response levels, fatalities, and economic losses. The inclusion of teleseismic data into this framework underscores its extensive applicability for rapid loss assessments, even in regions lacking local seismic data. Through comparisons with station observation waveforms and government-reported loss, the validity and practicality of the framework were substantiated. It plays a vital role in assisting emergency decisions, optimizing resource allocation, and further mitigating losses.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00037-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142762979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-02DOI: 10.1038/s44304-024-00043-6
Djacinto Monteiro dos Santos, Aline M. de Oliveira, Ediclê S. F. Duarte, Julia A. Rodrigues, Lucas S. Menezes, Ronaldo Albuquerque, Fabio de O. Roque, Leonardo F. Peres, Judith J. Hoelzemann, Renata Libonati
{"title":"Author Correction: Compound dry-hot-fire events connecting Central and Southeastern South America: an unapparent and deadly ripple effect","authors":"Djacinto Monteiro dos Santos, Aline M. de Oliveira, Ediclê S. F. Duarte, Julia A. Rodrigues, Lucas S. Menezes, Ronaldo Albuquerque, Fabio de O. Roque, Leonardo F. Peres, Judith J. Hoelzemann, Renata Libonati","doi":"10.1038/s44304-024-00043-6","DOIUrl":"10.1038/s44304-024-00043-6","url":null,"abstract":"","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-1"},"PeriodicalIF":0.0,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00043-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142758120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-22DOI: 10.1038/s44304-024-00034-7
Thomas J. Jones, Harry Nyce Jr., Yannick Le Moigne, Glyn Williams-Jones, Deanna Nyce
Indigenous peoples are widely affected by natural hazards and their history and knowledge can directly inform on past events and mitigation strategies. Here we show how effective co-creation of resources and bi-lateral knowledge exchange between natural hazard researchers and local Indigenous communities provides an effective, equitable, and sustainable way to conduct research.
{"title":"Rethinking natural hazards research and engagement to include co-creation with Indigenous communities","authors":"Thomas J. Jones, Harry Nyce Jr., Yannick Le Moigne, Glyn Williams-Jones, Deanna Nyce","doi":"10.1038/s44304-024-00034-7","DOIUrl":"10.1038/s44304-024-00034-7","url":null,"abstract":"Indigenous peoples are widely affected by natural hazards and their history and knowledge can directly inform on past events and mitigation strategies. Here we show how effective co-creation of resources and bi-lateral knowledge exchange between natural hazard researchers and local Indigenous communities provides an effective, equitable, and sustainable way to conduct research.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00034-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142679961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-14DOI: 10.1038/s44304-024-00032-9
Mohammad Ahmadi Gharehtoragh, David R. Johnson
Planners managing coastal flood risk under a constrained computational budget face a tradeoff. Simulating many time periods or scenarios limits how many storm simulations can be run on each landscape. In this analysis, we present a deep learning model to predict storm surge as a function of storm parameters but also landscape features and boundary conditions (e.g., sea level). It is trained on peak surge elevations from Advanced Circulation (ADCIRC) hydrodynamic simulations of coastal Louisiana in a 2020 baseline and decadal periods from 2030 to 2070 under two morphological and climate scenarios. Leave-one-landscape-out cross-validation yielded a 0.086-m RMSE and 0.050-m MAE over 90 storms per landscape and 94,013 geospatial locations. A two-sided Kolmogorov-Smirnov test comparing annual exceedance probability (AEP) estimates from the model predictions to ADCIRC simulations rejected the null hypothesis that the predicted and ADCIRC AEP values were drawn from the same distribution only 1.1% of the time.
{"title":"Using surrogate modeling to predict storm surge on evolving landscapes under climate change","authors":"Mohammad Ahmadi Gharehtoragh, David R. Johnson","doi":"10.1038/s44304-024-00032-9","DOIUrl":"10.1038/s44304-024-00032-9","url":null,"abstract":"Planners managing coastal flood risk under a constrained computational budget face a tradeoff. Simulating many time periods or scenarios limits how many storm simulations can be run on each landscape. In this analysis, we present a deep learning model to predict storm surge as a function of storm parameters but also landscape features and boundary conditions (e.g., sea level). It is trained on peak surge elevations from Advanced Circulation (ADCIRC) hydrodynamic simulations of coastal Louisiana in a 2020 baseline and decadal periods from 2030 to 2070 under two morphological and climate scenarios. Leave-one-landscape-out cross-validation yielded a 0.086-m RMSE and 0.050-m MAE over 90 storms per landscape and 94,013 geospatial locations. A two-sided Kolmogorov-Smirnov test comparing annual exceedance probability (AEP) estimates from the model predictions to ADCIRC simulations rejected the null hypothesis that the predicted and ADCIRC AEP values were drawn from the same distribution only 1.1% of the time.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00032-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142637010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-08DOI: 10.1038/s44304-024-00031-w
Djacinto Monteiro dos Santos, Aline M. de Oliveira, Ediclê S. F. Duarte, Julia A. Rodrigues, Lucas S. Menezes, Ronaldo Albuquerque, Fabio de O. Roque, Leonardo F. Peres, Judith J. Hoelzemann, Renata Libonati
South America has experienced severe compound drought-heatwaves (CDHW), exacerbating fires. Recently, the unprecedented Pantanal 2020 fire season (P20F), burning a third of the biome, resulted in well-reported local impacts on the ecosystem, economy, and health. Nevertheless, the long-range ripple effects of this event remain unknown. We investigated the P20F-related cascading hazards, integrating models, observational and satellite-based data. P20F-related smoke elevated PM2.5 levels in the SA’s most populated area, exceeding WHO guidelines by up to 600%. Smoke-induced air pollution episodes coincided with widespread heatwaves, amplifying health risks. The mortality burden attributable to this multi-hazard short-term (14 days) exposure was estimated to be 2150 premature deaths (21% increase above expected levels). Our findings highlight that the impacts of CDHW-fires in SA are beyond the local level, implying growing challenges for risk management and public health and the need for governance based on telecoupled flows, linking different systems over multiple scales.
{"title":"Compound dry-hot-fire events connecting Central and Southeastern South America: an unapparent and deadly ripple effect","authors":"Djacinto Monteiro dos Santos, Aline M. de Oliveira, Ediclê S. F. Duarte, Julia A. Rodrigues, Lucas S. Menezes, Ronaldo Albuquerque, Fabio de O. Roque, Leonardo F. Peres, Judith J. Hoelzemann, Renata Libonati","doi":"10.1038/s44304-024-00031-w","DOIUrl":"10.1038/s44304-024-00031-w","url":null,"abstract":"South America has experienced severe compound drought-heatwaves (CDHW), exacerbating fires. Recently, the unprecedented Pantanal 2020 fire season (P20F), burning a third of the biome, resulted in well-reported local impacts on the ecosystem, economy, and health. Nevertheless, the long-range ripple effects of this event remain unknown. We investigated the P20F-related cascading hazards, integrating models, observational and satellite-based data. P20F-related smoke elevated PM2.5 levels in the SA’s most populated area, exceeding WHO guidelines by up to 600%. Smoke-induced air pollution episodes coincided with widespread heatwaves, amplifying health risks. The mortality burden attributable to this multi-hazard short-term (14 days) exposure was estimated to be 2150 premature deaths (21% increase above expected levels). Our findings highlight that the impacts of CDHW-fires in SA are beyond the local level, implying growing challenges for risk management and public health and the need for governance based on telecoupled flows, linking different systems over multiple scales.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-13"},"PeriodicalIF":0.0,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00031-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-07DOI: 10.1038/s44304-024-00033-8
J. Martí
Volcanic eruptions are typically preceded by unrest, marked by increased seismicity, ground deformation, and gas emissions. Unrest can last from decades to minutes. Accurate eruption forecasting relies on real-time monitoring and understanding the volcano’s past behavior. Long-term hazard assessments, combined with real-time data, help identify probable eruptive scenarios (short-term hazard assessment), improving forecasting during volcanic crises.
{"title":"From rest to eruption: How we should anticipate volcanic eruptions","authors":"J. Martí","doi":"10.1038/s44304-024-00033-8","DOIUrl":"10.1038/s44304-024-00033-8","url":null,"abstract":"Volcanic eruptions are typically preceded by unrest, marked by increased seismicity, ground deformation, and gas emissions. Unrest can last from decades to minutes. Accurate eruption forecasting relies on real-time monitoring and understanding the volcano’s past behavior. Long-term hazard assessments, combined with real-time data, help identify probable eruptive scenarios (short-term hazard assessment), improving forecasting during volcanic crises.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00033-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-07DOI: 10.1038/s44304-024-00030-x
Yang Shi, Yilong Li, Zhenguo Zhang
Earthquakes in the Taiwan region have caused significant economic losses. We develop a model to assess seismic economic losses in the Taiwan region using the records of economic losses caused by historical earthquakes. Unlike existing models, we introduce Gross National Income Per Capita (GNIPC) as a parameter that responds to the influence of socio-economic development. The results show that our model can accurately estimate the earthquake economic losses in Taiwan region. The difference between the results of this model and those of existing models is evident, indicating differences between the Taiwan region and mainland China regarding geological background, seismic tectonics, and social resistance to earthquakes. The prediction results also imply that the society significantly underestimates the seismic economic losses in the Taiwan region. Our model can help the Taiwan region in disaster prevention and preparedness, contingency planning, allocation of relief resources, and post-disaster socio-economic recovery.
{"title":"Estimation of economic loss by earthquakes in Taiwan Region","authors":"Yang Shi, Yilong Li, Zhenguo Zhang","doi":"10.1038/s44304-024-00030-x","DOIUrl":"10.1038/s44304-024-00030-x","url":null,"abstract":"Earthquakes in the Taiwan region have caused significant economic losses. We develop a model to assess seismic economic losses in the Taiwan region using the records of economic losses caused by historical earthquakes. Unlike existing models, we introduce Gross National Income Per Capita (GNIPC) as a parameter that responds to the influence of socio-economic development. The results show that our model can accurately estimate the earthquake economic losses in Taiwan region. The difference between the results of this model and those of existing models is evident, indicating differences between the Taiwan region and mainland China regarding geological background, seismic tectonics, and social resistance to earthquakes. The prediction results also imply that the society significantly underestimates the seismic economic losses in the Taiwan region. Our model can help the Taiwan region in disaster prevention and preparedness, contingency planning, allocation of relief resources, and post-disaster socio-economic recovery.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00030-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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