Future changes in the seasonal evolution of the El Niño-Southern Oscillation (ENSO) during its onset and decay phases have received little attention by the research community. This work investigates the projected changes in the spatio-temporal evolution of El Niño events in the 21 Century (21 C), using a multi-model ensemble of coupled general circulation models subjected to anthropogenic forcing. Here we show that El Niño is projected to (1) grow at a faster rate, (2) persist longer over the eastern and far eastern Pacific, and (3) have stronger and distinct remote impacts via teleconnections. These changes are attributable to significant changes in the tropical Pacific mean state, dominant ENSO feedback processes, and an increase in stochastic westerly wind burst forcing in the western equatorial Pacific, and may lead to more significant and persistent global impacts of El Niño in the future.
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http://dx.doi.org/10.1038/s41467-022-29519-7 | DOI Listing |
Background: Investigators and funding organizations desire knowledge on topics and trends in publicly funded research but current efforts for manual categorization have been limited in breadth and depth of understanding.
Purpose: We present a semi-automated analysis of 21 years of R-type National Cancer Institute (NCI) grants to departments of radiation oncology and radiology using natural language processing (NLP).
Methods: We selected all non-education R-type NCI grants from 2000 to 2020 awarded to departments of radiation oncology/radiology with affiliated schools of medicine.
Cureus
December 2024
Zebrafish Research Unit, Mahatma Gandhi Medical Advanced Research Institute, Sri Balaji Vidyapeeth (Deemed-to-be-University), Pondicherry, IND.
Low- and middle-income countries (LMICs) are increasingly challenged by the rising burden of medicolegal cases. Traditional forensic infrastructure and in vivo rodent models often have significant limitations due to high costs and ethical concerns. As a result, zebrafish () are gaining popularity as an attractive alternative model for LMICs because of their cost-effectiveness and practical advantages.
View Article and Find Full Text PDFJ Affect Disord
January 2025
Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No.38, Xueyuan Road, Haidian District, Beijing 100191, China; Key Laboratory of Epidemiology of Major Diseases, Peking University, Ministry of Education, No.38, Xueyuan Road, Haidian District, Beijing 100191, China; Institute for Global Health and Development, Peking University, No.5 Yiheyuan Road, Haidian District, Beijing 100871, China; Global Center for Infectious Disease and Policy Research & Global Health and Infectious Diseases Group, Peking University, No.38, Xueyuan Road, Haidian District, Beijing 100191, China. Electronic address:
Aims: To estimate the burden of major depressive disorder (MDD) among older adults and project its prevalence through 2050.
Methods: Using data from the Global Burden of Disease Study 2021, we calculated age-standardized rates (ASRs) for the incidence, prevalence, and years lived with disability (YLDs) of MDD among people aged ≥60 years from 1990 to 2021. Trends were analyzed using average annual percentage changes (AAPCs).
Neural Netw
January 2025
School of Software, Shandong University, Jinan 250101, China; Shandong Provincial Laboratory of Future Intelligence and Financial Engineering, Yantai 264005, China. Electronic address:
Long time series forecasting has extensive applications in various fields such as power dispatching, traffic control, and weather forecasting. Recently, models based on the Transformer architecture have dominated the field of time series forecasting. However, these methods lack the ability to handle the correlation of multi-scale information and the interaction of information between variables in model design.
View Article and Find Full Text PDFBiofabrication
January 2025
CÚRAM, Research Ireland Centre for Medical Devices, University of Galway, Galway, Ireland.
Despite significant advances in bioprinting technology, current hardware platforms lack the capability for process monitoring and quality control. This limitation hampers the translation of the technology into industrial GMP-compliant manufacturing settings. As a key step towards a solution, we developed a novel bioprinting platform integrating a high-resolution camera formonitoring of extrusion outcomes during embedded bioprinting.
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