Candace Owens leaks Erika Kirk phone call: 'It makes my skin crawl' Why I'm more concerned than ever about what Barron Trump is doing behind closed doors: KENNEDY Revealed: Truth behind Barron Trump's dramatic Facetime phone call with'girlfriend' and the British public school-educated MMA fighter who beat her up Kim Kardashian breaks silence on why Prince Harry and Meghan Markle photos were deleted from Kris Jenner's birthday post Nicki Minaj flashes dagger-long nails as she clutches Trump's hand after gushing she's his No. 1 fan Telling detail stitched into Melania's Dior dress that hints at her true ambitions, as the First Lady rings the New York Stock Exchange bell: JANE TIPPETT Hilarious live gaffe on David Muir's World News Tonight that'triggered behind the scenes meltdown' Extraordinary transformation of beloved child star who has'self-canceled' and ditched Hollywood to live off grid in POVERTY as'Catholic extremist' He's the famed Glambot director whose slow-mo videos of celebs go viral. But now, as he's forced to apologize for leaked emails... nasty rumors are swirling'Greedy pig' Harry Styles is shamefully exploiting obsessed women. I know... because it happened to me: LIZ JONES Bruce Willis' wife Emma makes heartbreaking admission about star's dementia battle Julie Newmar, 92, who played Catwoman on TV's Batman in the '60s, looks amazing in rare sighting Woke CNN guest scolded for vicious personal attack on co-panelist Kevin O'Leary Scientists are about to DRILL into the most fragile part of Antarctica's Doomsday Glacier READ MORE: Doomsday Clock ticks forward... taking us closer to annihilation Scientists are about to drill into the most inaccessible and least-understood part of the Thwaites Glacier. Measuring around the same size as Great Britain, this huge mass of ice in West Antarctica is one of the largest and fastest changing glaciers in the world. Worryingly, research has shown that if it collapses, the glacier will cause global sea levels to rise by a whopping 2.1ft (65cm) - plunging entire communities underwater.

An iceberg sealed the penguin colony's entrance, triggering a 70% survival drop. A group of Emperor penguin chicks is walking on the fast ice at the Emperor penguin colony at Snow Hill Island in the Weddell Sea in Antarctica. Breakthroughs, discoveries, and DIY tips sent six days a week. A massive iceberg has triggered a catastrophic die-off of Emperor Penguin chicks in Antarctica, blocking thousands of parents from reaching their young. The event claimed the lives of approximately 14,000 chicks at the Coulman Island colony in the Ross Sea, the region's largest breeding ground.

An analysis of the expansion of cracks in the Thwaites Glacier over the past 20 years suggests that a total collapse could be only a matter of time. Known as the "Doomsday Glacier," the Thwaites Glacier in Antarctica is one of the most rapidly changing glaciers on Earth, and its future evolution is one of the biggest unknowns when it comes to predicting global sea level rise. The eastern ice shelf of the Thwaites Glacier is supported at its northern end by a ridge of the ocean floor. However, over the past two decades, cracks in the upper reaches of the glacier have increased rapidly, weakening its structural stability. A new study by the International Thwaites Glacier Collaboration (ITGC) presents a detailed record of this gradual collapse process.

Accurate yet efficient surrogate models are essential for large-scale simulations of partial differential equations (PDEs), particularly for uncertainty quantification (UQ) tasks that demand hundreds or thousands of evaluations. We develop a physics-inspired graph neural network (GNN) surrogate that operates directly on unstructured meshes and leverages the flexibility of graph attention. To improve both training efficiency and generalization properties of the model, we introduce a domain decomposition (DD) strategy that partitions the mesh into subdomains, trains local GNN surrogates in parallel, and aggregates their predictions. We then employ transfer learning to fine-tune models across subdomains, accelerating training and improving accuracy in data-limited settings. Applied to ice sheet simulations, our approach accurately predicts full-field velocities on high-resolution meshes, substantially reduces training time relative to training a single global surrogate model, and provides a ripe foundation for UQ objectives. Our results demonstrate that graph-based DD, combined with transfer learning, provides a scalable and reliable pathway for training GNN surrogates on massive PDE-governed systems, with broad potential for application beyond ice sheet dynamics.

Plus: Donald Trump wants to outlaw individual states' right to regulate AI The International Energy Agency recently released the latest version of the World Energy Outlook, the annual report that takes stock of the current state of global energy and looks toward the future. It contains some interesting insights and a few surprising figures about electricity, grids, and the state of climate change. Let's dig into some numbers . This article is from The Spark, MIT Technology Review's weekly climate newsletter. Everything is a conspiracy theory now. Our latest series " The New Conspiracy Age " delves into how conspiracies have gripped the White House, turning fringe ideas into dangerous policy, and how generative AI is altering the fabric of truth.

We introduce KAN-GCN, a fast and accurate emulator for ice sheet modeling that places a Kolmogorov-Arnold Network (KAN) as a feature-wise calibrator before graph convolution networks (GCNs). The KAN front end applies learnable one-dimensional warps and a linear mixing step, improving feature conditioning and nonlinear encoding without increasing message-passing depth. We employ this architecture to improve the performance of emulators for numerical ice sheet models. Our emulator is trained and tested using 36 melting-rate simulations with 3 mesh-size settings for Pine Island Glacier, Antarctica. Across 2- to 5-layer architectures, KAN-GCN matches or exceeds the accuracy of pure GCN and MLP-GCN baselines. Despite a small parameter overhead, KAN-GCN improves inference throughput on coarser meshes by replacing one edge-wise message-passing layer with a node-wise transform; only the finest mesh shows a modest cost. Overall, KAN-first designs offer a favorable accuracy vs. efficiency trade-off for large transient scenario sweeps.

AOC hit by shockingly crude sex insult by White House after she mocked'TINY' Stephen Miller Biden ordered CIA cover-up of his'corrupt' business ties to Ukraine, astonishing secret files show NYC girls aged 12 and 13 meet tragic end after going subway surfing across Williamsburg Bridge at 3.10am ERIC TRUMP: The darkest day in my dad's marriage to Melania... before the ugly truth was exposed More girls are starting their periods younger than ever before - scientists think they've finally found what's causing it Taylor Swift reveals truth behind raunchy song about Travis Kelce's manhood Meghan is accused of'giggling as model stumbles on the catwalk': More Paris Fashion Week disasters emerge, including awkward moment with Kristin Scott Thomas The TRUTH to the doting mother who slaughtered her children and husband told by those she'd been quietly tormenting for years The troubled background of delivery man stabbed by Mark Sanchez... as he launches million-dollar lawsuit and sparks civil war at Fox Revealed: Which slimming jab REALLY works best. The doctors' ultimate expert guide on which to pick, how to save money, beat every side effect... and what you need to know about the'golden dose' I haven't heard that name in so long' Ominous warning for humanity as birds suddenly adopt'unsettling' behavior And a humiliating lifeline: Backroom secrets of Taylor Swift and Blake Lively... after hit new song Bottled water contains dangerous levels of microplastics that lodge in vital organs and raise cancer risk', scientists warn Sea level rise could plunge 100 MILLION buildings underwater, warn scientists - so, is your home at risk? Rising sea levels could plunge more than 100 million buildings underwater by 2100, scientists have warned. The experts in Canada estimated how many buildings in Africa, Southeast Asia and Central and South America would be flooded by different sea level changes. Their assessment found that sea level rises of just 1.6 feet (0.5 metres) would flood three million buildings in the global south alone.

In the realm of aerial imaging, the ability to detect small objects is pivotal for a myriad of applications, encompassing environmental surveillance, urban design, and crisis management. Leveraging RetinaNet, this work unveils DDR-Net: a data-driven, deep-learning model devised to enhance the detection of diminutive objects. DDR-Net introduces novel, data-driven techniques to autonomously ascertain optimal feature maps and anchor estimations, cultivating a tailored and proficient training process while maintaining precision. Additionally, this paper presents an innovative sampling technique to bolster model efficacy under limited data training constraints. The model's enhanced detection capabilities support critical applications including wildlife and habitat monitoring, traffic flow optimization, and public safety improvements through accurate identification of small objects like vehicles and pedestrians. DDR-Net significantly reduces the cost and time required for data collection and training, offering efficient performance even with limited data. Empirical assessments over assorted aerial avian imagery datasets demonstrate that DDR-Net markedly surpasses RetinaNet and alternative contemporary models. These innovations advance current aerial image analysis technologies and promise wide-ranging impacts across multiple sectors including agriculture, security, and archaeology.