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  • Space weather in focus after Airbus fleet recall, experts raise questions about solar flare theory

    Space weather in focus after Airbus fleet recall, experts raise questions about solar flare theory

    Aerospace giant Airbus is recalling about half of its global fleet over a commercial plane’s sudden altitude drop, bringing into sharp focus the importance of space weather in flight safety, even as experts raise questions about the company’s…

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  • My cultural awakening: Jonathan Groff inspired me to overcome my stammer | Culture

    My cultural awakening: Jonathan Groff inspired me to overcome my stammer | Culture

    My first encounter with Broadway actor Jonathan Groff was innocuous. Stuck in the wilds of Donegal for two weeks as part of teacher training, I listened to Broadway musicals while the rest of the lads watched the Gaelic fixtures and got drunk. I…

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  • Science history: Female chemist initially barred from research helps helps develop drug for remarkable-but-short-lived recovery in children with leukemia — Dec. 6, 1954

    Science history: Female chemist initially barred from research helps helps develop drug for remarkable-but-short-lived recovery in children with leukemia — Dec. 6, 1954

    Milestone: Chemotherapy agent sends leukemia into remission

    Date: Dec. 6, 1954

    Where: Sloan Kettering Institute and Weill Cornell Medical College in New York

    Who: Gertrude Elion and colleagues

    In 1954, researchers described a new drug that sent…

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  • Microsoft quietly make big changes to its employee performance reviews, company has removed…

    Microsoft quietly make big changes to its employee performance reviews, company has removed…

    Microsoft has removed diversity and inclusion from mandatory employee performance reviews, a significant shift from its 2020 commitments. The company also won’t publish its annual diversity report this year, citing a move to more dynamic…

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  • Indian envoy reaffirms support for cyclone-hit Sri Lanka in meeting with corporate leaders

    Indian envoy reaffirms support for cyclone-hit Sri Lanka in meeting with corporate leaders

    Houses damaged by the overflowing Mahaweli River following Cyclone Ditwah, in Kandy, Sri Lanka
    | Photo Credit: Reuters

    Indian High…

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  • Mitchell Starc’s unbeaten 46 extends Australia’s lead to 116 on Day 3 of 2nd Ashes test

    Mitchell Starc’s unbeaten 46 extends Australia’s lead to 116 on Day 3 of 2nd Ashes test

    The eighth-wicket pair put on 33 runs, with Starc taking Australia’s total past 400 with an attacking boundary against Brydon Carse in the 79th over, before Carey was out in the third over with the new ball.

    Carey faced 69 deliveries and hit six…

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  • Le Traon, P. Y. et al. From observation to information and users: The Copernicus Marine Service perspective. Front. Mar. Sci. 6, 234 (2019).

    Google Scholar 

  • Sun, R. et al. SKRIPS v1.0: A regional coupled ocean-atmosphere modeling framework (MITgcm-WRF) using ESMF/NUOPC, description and preliminary results for the Red Sea. Geosci. Model Dev. 12, 4221–4244 (2019).

    Google Scholar 

  • Sakamoto, K. et al. Development of a 2-km resolution ocean model covering the coastal seas around Japan for operational application. Ocean Dyn. 69, 1181–1202 (2019).

    Google Scholar 

  • Ciliberti, S. A. et al. Monitoring and forecasting the ocean state and biogeochemical processes in the Black Sea: Recent developments in the Copernicus Marine Service. J. Mar. Sci. Eng. 9, 1146 (2021).

    Google Scholar 

  • Kärnä, T. et al. Operational marine forecast model for the Baltic Sea. Nemo-Nordic 2.0. Geosci. Model Dev. 14, 5731–5749 (2021).

  • Zhu, X. et al. Improvements in the regional South China Sea operational oceanography forecasting system (SCSOFSv2). Geosci. Model Dev. 15, 995–1015 (2022).

    Google Scholar 

  • Bruschi, A. et al. Indexes for the assessment of bacterial pollution in bathing waters from point sources: The northern Adriatic Sea CADEAU service. J. Environ. Manag. 293, 112878 (2021).

    Google Scholar 

  • Liubartseva, S. et al. Modeling chronic oil pollution from ships. Mar. Pollut. Bull. (2023).

  • Mannarini, G., Salinas, M. L., Carelli, L., Petacco, N. & Orović, J. VISIR-2: Ship weather routing in Python. Geosci. Model Dev. 17, 4355–4382 (2024).

    Google Scholar 

  • Coppini, G. et al. The Mediterranean forecasting system-Part 1: Evolution and performance. Ocean Sci. 19, 1483–1516 (2023).

    Google Scholar 

  • Bi, K. et al. Accurate medium-range global weather forecasting with 3D neural networks. Nature 619, 533–538 (2023).

    Google Scholar 

  • Nguyen, T. et al. Scaling transformer neural networks for skillful and reliable medium-range weather forecasting. Adv. Neural Inf. Process. Syst. 37, 68740–68771 (2024).

    Google Scholar 

  • Pathak, J. et al. FourCastNet: A global data-driven high-resolution weather model using adaptive Fourier neural operators. arXiv preprint arXiv:2202.11214 (2022).

  • Keisler, R. Forecasting global weather with graph neural networks. arXiv preprint arXiv:2202.07575 (2022).

  • Lam, R. et al. Learning skillful medium-range global weather forecasting. Science 382, 1416–1421 (2023).

    Google Scholar 

  • Oskarsson, J., Landelius, T., Deisenroth, M. & Lindsten, F. Probabilistic weather forecasting with hierarchical graph neural networks. Adv. Neural Inf. Process. Syst. 37, 41577–41648 (2024).

    Google Scholar 

  • Dheeshjith, S. et al. Samudra: An AI global ocean emulator for climate. Geophys. Res. Lett. 52(10), e2024GL114318 (2025).

    Google Scholar 

  • Wang, C. et al. Coupled ocean-atmosphere dynamics in a machine learning Earth system model. arXiv preprint arXiv:2406.08632 (2024).

  • Guo, Z. et al. Data-driven global ocean modeling for seasonal to decadal prediction. arXiv preprint arXiv:2405.15412 (2024).

  • Wang, X. et al. XiHe: A data-driven model for global ocean eddy-resolving forecasting. arXiv preprint arXiv:2402.02995 (2024).

  • Aouni, A. E. et al. GLONET: Mercator’s end-to-end neural forecasting system. arXiv preprint arXiv:2412.05454 (2024).

  • Cui, Y. et al. Forecasting the eddying ocean with a deep neural network. Nat. Commun. 16, 2268 (2025).

    Google Scholar 

  • Andersson, T. R. et al. Seasonal Arctic sea ice forecasting with probabilistic deep learning. Nat. Commun. 12, 5124 (2021).

    Google Scholar 

  • Chattopadhyay, A., Gray, M., Wu, T., Lowe, A. B. & He, R. OceanNet: A principled neural operator-based digital twin for regional oceans. Sci. Rep. 14, 21181 (2024).

    Google Scholar 

  • Subel, A. & Zanna, L. Building ocean climate emulators. arXiv preprint arXiv:2402.04342 (2024).

  • Sanchez-Gonzalez, A. et al. Learning to simulate complex physics with graph networks. In International Conference on Machine Learning. 8459–8468 (2020).

  • Marchesiello, P., McWilliams, J. C. & Shchepetkin, A. Open boundary conditions for long-term integration of regional oceanic models. Ocean Model. 3, 1–20 (2001).

    Google Scholar 

  • Escudier, R. et al. A high resolution reanalysis for the Mediterranean Sea. Front. Earth Sci. 9, 702285 (2021).

    Google Scholar 

  • Hersbach, H. et al. ERA5 monthly averaged data on single levels from 1940 to present. In Copernicus Climate Change Service (C3S) Climate Data Store (CDS) (2023).

  • Molteni, F., Buizza, R., Palmer, T. N. & Petroliagis, T. The ECMWF ensemble prediction system: Methodology and validation. Q. J. R. Meteorol. Soc. 122, 73–119 (1996).

    Google Scholar 

  • Lang, S. et al. AIFS – ECMWF’s data-driven forecasting system. arXiv preprint arXiv:2406.01465 (2024).

  • ECMWF. Plans for high resolution forecast (HRES) and ensemble forecast (ENS). In focus (2024). https://www.ecmwf.int/en/about/media-centre/focus/2024/plans-high-resolution-forecast-hres-and-ensemble-forecast-ens.

  • Nardelli, B. B., Tronconi, C., Pisano, A. & Santoleri, R. High and ultra-high resolution processing of satellite sea surface temperature data over southern European seas in the framework of MyOcean project. Remote Sens. Environ. 129, 1–16 (2013).

    Google Scholar 

  • Hobday, A. J. et al. A hierarchical approach to defining marine heatwaves. Prog. Oceanogr. 141, 227–238 (2016).

    Google Scholar 

  • Kochkov, D. et al. Neural general circulation models for weather and climate. Nature 632, 1060–1066 (2024).

    Google Scholar 

  • Marshall, J. & Schott, F. Open-ocean convection: Observations, theory, and models. Rev. Geophys. 37, 1–64 (1999).

    Google Scholar 

  • Large, W. G., McWilliams, J. C. & Doney, S. C. Oceanic vertical mixing: A review and a model with a nonlocal boundary layer parameterization. Rev. Geophys. 32, 363–403 (1994).

    Google Scholar 

  • Wunsch, C. & Stammer, D. Atmospheric loading and the oceanic inverted barometer effect. Rev. Geophys. 35, 79–107 (1997).

    Google Scholar 

  • Gill, A. E. Atmosphere–Ocean Dynamics (Academic Press, 1982).

  • Clementi, E. et al. Coupling hydrodynamic and wave models: first step and sensitivity experiments in the Mediterranean Sea. Ocean Dyn. 67, 1293–1312 (2017).

    Google Scholar 

  • McDonagh, B., Clementi, E., Goglio, A. C. & Pinardi, N. The characteristics of tides and their effects on the general circulation of the Mediterranean Sea. Ocean Sci. 20, 1051–1066 (2024).

    Google Scholar 

  • Rühling Cachay, S., Zhao, B., Joren, H. & Yu, R. Dyffusion: A dynamics-informed diffusion model for spatiotemporal forecasting. Adv. Neural Inf. Process. Syst. 36, 45259–45287 (2023).

    Google Scholar 

  • Andrae, M., Landelius, T., Oskarsson, J. & Lindsten, F. Continuous ensemble weather forecasting with diffusion models. In International Conference on Learning Representations (2025).

  • Nipen, T. N. et al. Regional data-driven weather modeling with a global stretched-grid. arXiv preprint arXiv:2409.02891 (2024).

  • Adamov, S. et al. Building machine learning limited area models: Kilometer-scale weather forecasting in realistic settings. arXiv preprint arXiv:2504.09340 (2025).

  • Nguyen, T., Brandstetter, J., Kapoor, A., Gupta, J. K. & Grover, A. ClimaX: A foundation model for weather and climate. In International Conference on Machine Learning (2023).

  • Bodnar, C. et al. A foundation model for the Earth system. Nature 1–8 (2025).

  • Price, I. et al. Probabilistic weather forecasting with machine learning. Nature 637, 84–90 (2025).

    Google Scholar 

  • Larsson, E., Oskarsson, J., Landelius, T. & Lindsten, F. Diffusion-LAM: Probabilistic limited area weather forecasting with diffusion. arXiv preprint arXiv:2502.07532 (2025).

  • Fortunato, M., Pfaff, T., Wirnsberger, P., Pritzel, A. & Battaglia, P. Multiscale meshgraphnets. arXiv preprint arXiv:2210.00612 (2022).

  • Battaglia, P., Pascanu, R., Lai, M., Jimenez Rezende, D. et al. Interaction networks for learning about objects, relations and physics. Adv. Neural Inf. Process. Syst. 29 (2016).

  • Ramachandran, P., Zoph, B. & Le, Q. V. Searching for activation functions. arXiv preprint arXiv:1710.05941 (2017).

  • Ba, J., Kiros, J. & Hinton, G. Layer normalization. arXiv preprint arXiv:1607.06450 (2016).

  • Loshchilov, I. & Hutter, F. Decoupled weight decay regularization. In International Conference on Learning Representations (2019).

  • Madec, G. et al. NEMO ocean engine. In Scientific Notes of Climate Modelling Center. Vol. 27 (2017).

  • WAVEWATCH III Development Group (WW3DG). User Manual and System Documentation of WAVEWATCH III Version 6.07. In Technical Note 333, NOAA/NWS/NCEP/MMAB, College Park, MD, USA (2019).

  • Dobricic, S. & Pinardi, N. An oceanographic three-dimensional variational data assimilation scheme. Ocean Model. 22, 89–105 (2008).

    Google Scholar 

  • Weatherall, P. et al. A new digital bathymetric model of the world’s oceans. Earth Sp. Sci. 2, 331–345 (2015).

    Google Scholar 

  • Hellerman, S. & Rosenstein, M. Normal monthly wind stress over the world ocean with error estimates. J. Phys. Oceanogr. 13, 1093–1104 (1983).

    Google Scholar 

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  • U.S. CDC’s advisory committee votes to drop universal Hepatitis B birth-dose recommendation-Xinhua

    LOS ANGELES, Dec. 5 (Xinhua) — The U.S. Centers for Disease Control and Prevention (CDC)’s Advisory Committee on Immunization Practices (ACIP) voted on Friday to end the long-standing recommendation that all newborns receive a Hepatitis B…

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  • Placenta Previa is Associated with Maternal Depression, Anxiety, and P

    Placenta Previa is Associated with Maternal Depression, Anxiety, and P

    Introduction

    Placenta previa (PP) is a major obstetric complication associated with increased risks of maternal morbidity, hemorrhage, and perinatal mortality. PP is a condition where the placenta is positioned such that it fully or partially…

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  • England nemesis Starc stretches Australia lead in Gabba Ashes Test – France 24

    1. England nemesis Starc stretches Australia lead in Gabba Ashes Test  France 24
    2. The Ashes 2025 LIVE: Australia vs England, second Test, Brisbane – cricket score, radio & highlights  BBC
    3. Ashes 2025-26 – Australia wait to count cost of crazy floodlit…

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