This Is the Nuclear-Powered Ship Deployed in Trump's War on Drug Boats The USS is a $13 billion aircraft carrier sailing to the Caribbean with nuclear propulsion, an electromagnetic plane launcher, and 90 aircraft onboard. The Pentagon has deployed the USS Gerald R. Ford in an anti-drug trafficking mission in the Caribbean. The USS, the US Navy's most advanced aircraft carrier, is heading to the Caribbean Sea as part of a Pentagon strategy it says is meant to strengthen the fight against drug trafficking in South America. The news was confirmed late last week by Sean Parnell, assistant secretary of defense for public affairs, through his social networks . In his message, he explained that the deployment of the "will strengthen the United States' ability to detect, monitor and dismantle illicit actors and activities that compromise the security and prosperity of US territory, as well as our stability in the Western Hemisphere."

China will soon have a new Five Year Plan. Here's how they have changed the world so far China's top leaders are gathering in Beijing this week to decide on the country's key goals and aspirations for the rest of the decade. Every year or so, the country's highest political body, the Central Committee of the Chinese Communist Party, convenes for a week of meetings, also known as a Plenum. What it decides at this one will eventually form the basis of China's next Five Year Plan - the blueprint that the world's second largest economy will follow between 2026 and 2030. The full plan won't come until next year, but officials are likely to hint at its contents on Wednesday and have previously given more details within a week of that.

Disney superfan, 31, vanishes from her Midwest home months after announcing pregnancy... then horrific discovery is made at Walt Disney World Pete Hegseth's jet makes emergency landing in Britain after high-stakes NATO summit on Russia-Ukraine war Doctor's husband'was watching X-rated videos in his house while daughter, two, died in roasting car outside' Bella Hadid's health battle takes dark turn: Loved ones reveal hellish new details about'missing' model... as ominous texts emerge Trump hails'beautiful black women' strutting Chicago in MAGA hats Trump says he'll go to the Supreme Court to watch tariff arguments Charlie Kirk suspect invokes Bryan Kohberger as he makes clothing demand to seem'more human' America's saddest lost soul can no longer SPEAK and spends days hitting herself'after years of unspeakable abuse by gangs of men' Virginia Giuffre calls Prince Andrew'entitled' and claims duke saw having sex with her as his'birthright' in autobiography released after her death'You will DIE if you do not remove your breasts', doctors screamed at me. I refused and tried a new experimental therapy instead... now I'm cancer-free Warning over'life-threatening' storm brewing in Atlantic that could hit US Will Trump's Gaza peace deal fail? Policy expert MARK DUBOWITZ breaks down all the forces at play... and how the president can actually pull this off America's nuclear bombers spotted on mission over Venezuela as conflict escalates Astonishing interactive map lays bare where MILLIONS of homes will be submerged by water within a few years... are YOU at risk? The View's Joy Behar reveals the TRUTH behind her ageless appearance aged 83 Trump ORDERS troops to be paid as'hatchet man' floats 10,000 job cuts amid government shutdown America's nuclear bombers spotted on mission over Venezuela as conflict escalates READ MORE: Trump strikes'narco-terrorist' boat killing six as Venezuela warns of full-scale US invasion A trio of US B-52H Stratofortress bombers was spotted flying near Venezuelan airspace in what some analysts are calling a bold display of military power. Flight tracking data shows all three bombers departed from Louisiana's Barksdale Air Force Base in Shreveport, starting at 2:50am ET.

Doctor's husband'was watching X-rated videos in his house while daughter, two, died in roasting car outside' Dems hand out'Is he dead yet?' bracelet to child at Wisconsin farmers' market Warning over'life-threatening' storm brewing in Atlantic that could hit US Bella Hadid's health battle takes dark turn: Loved ones reveal hellish new details about'missing' model... as ominous texts emerge Florida's housing market is flashing a warning for the rest of the US America's saddest lost soul can no longer SPEAK and spends days hitting herself'after years of unspeakable abuse by gangs of men' Pete Hegseth's jet makes emergency landing after high-stakes NATO summit on Russia-Ukraine war'You will DIE if you do not remove your breasts', doctors screamed at me. I refused and tried a new experimental therapy instead... now I'm cancer-free Now scientists redefine'obese' - and they've made up to 60% more people'fat' Will Trump's Gaza peace deal fail? Policy expert MARK DUBOWITZ breaks down all the forces at play... and how the president can actually pull this off Shocking moment brazen gunman opens fire at Michigan businessman's Land Rover in daylight attack Astonishing interactive map lays bare where MILLIONS of homes will be submerged by water within a few years... are YOU at risk? America's most renowned'prophet' makes startling prediction about alien'mothership' Ugly divorce war between Mitt Romney's wealthy brother and estranged wife before she was found dead Virginia Guiffre calls Prince Andrew'entitled' and claims duke saw having sex with her as his'birthright' in autobiography released after her death Warning over'life-threatening' storm brewing in Atlantic that could hit US Meteorologists issued an alert on Thursday, warning of a tropical system forming in the Atlantic that could pose a threat in the coming weeks . AccuWeather is tracking a tropical wave off the coast of Africa, which is expected to reach the eastern Caribbean islands late this weekend. Tropical waves are clusters of scattered showers and thunderstorms that form over Africa or the Indian Ocean and slowly move west across the Atlantic Ocean.

Breakthroughs, discoveries, and DIY tips sent every weekday. The smelly, brown seaweed can put a damper on a day at the beach at best and hinder baby turtles on their way to the ocean at worst. Only about one in 1,000 sea turtle hatchlings survive to adulthood, and might be added to their already long list of challenges . The new findings detailed in a study published in the explores the role that this brown seaweed plays on vulnerable sea turtle populations. "For sea turtle hatchlings, reaching the ocean is already a race against time - and survival. Now, increasingly large mats of sargassum are adding new challenges to this critical journey," study co-author and Florida Atlantic University biologist Sarah Milton, said in a statement .

Storm surge forecasting plays a crucial role in coastal disaster preparedness, yet existing machine learning approaches often suffer from limited spatial resolution, reliance on coastal station data, and poor generalization. Moreover, many prior models operate directly on unstructured spatial data, making them incompatible with modern deep learning architectures. In this work, we introduce a novel approach that projects unstructured water elevation fields onto structured Red Green Blue (RGB)-encoded image representations, enabling the application of Convolutional Long Short Term Memory (ConvLSTM) networks for end-to-end spatiotemporal surge forecasting. Our model further integrates ground-truth wind fields as dynamic conditioning signals and topo-bathymetry as a static input, capturing physically meaningful drivers of surge evolution. Evaluated on a large-scale dataset of synthetic storms in the Gulf of Mexico, our method demonstrates robust 48-hour forecasting performance across multiple regions along the Texas coast and exhibits strong spatial extensibility to other coastal areas. By combining structured representation, physically grounded forcings, and scalable deep learning, this study advances the frontier of storm surge forecasting in usability, adaptability, and interpretability.

Sign up for the Slatest to get the most insightful analysis, criticism, and advice out there, delivered to your inbox daily. Summer just started, and the first significant heat wave of the season is almost over. Some 265 million people across the Midwest and the eastern United States have experienced a week of temperatures in the 90s and triple digits, with a slew of all-time records set on Tuesday. While extreme heat waves can be caused by any number of factors, this particular one is thanks to a phenomenon called a heat dome: a ridge of atmospheric pressure that settles over a region like, well, a dome. Or, as the National Weather Service's Alex Lamers so wonderfully described it to NPR, think of it as a lid placed over a grilled cheese, which, as we all know, makes the cheese melt much faster.

We present the challenging task of automatically creating a high-level Wikipedia-style article that aggregates information from multiple diverse videos about real-world events, such as natural disasters or political elections. Videos are intuitive sources for retrieval-augmented generation (RAG), but most contemporary RAG workflows focus heavily on text and existing methods for video-based summarization focus on low-level scene understanding rather than high-level event semantics. To close this gap, we introduce WikiVideo, a benchmark consisting of expert-written articles and densely annotated videos that provide evidence for articles' claims, facilitating the integration of video into RAG pipelines and enabling the creation of in-depth content that is grounded in multimodal sources. We further propose Collaborative Article Generation (CAG), a novel interactive method for article creation from multiple videos. CAG leverages an iterative interaction between an r1-style reasoning model and a VideoLLM to draw higher level inferences about the target event than is possible with VideoLLMs alone, which fixate on low-level visual features. We benchmark state-of-the-art VideoLLMs and CAG in both oracle retrieval and RAG settings and find that CAG consistently outperforms alternative methods, while suggesting intriguing avenues for future work.

Air pollution has become a major threat to human health, making accurate forecasting crucial for pollution control. Traditional physics-based models forecast global air pollution by coupling meteorology and pollution processes, using either online or offline methods depending on whether fully integrated with meteorological models and run simultaneously. However, the high computational demands of both methods severely limit real-time prediction efficiency. Existing deep learning (DL) solutions employ online coupling strategies for global air pollution forecasting, which finetune pollution forecasting based on pretrained atmospheric models, requiring substantial training resources. This study pioneers a DL-based offline coupling framework that utilizes bilinear pooling to achieve offline coupling between meteorological fields and pollutants. The proposed model requires only 13% of the parameters of DL-based online coupling models while achieving competitive performance. Compared with the state-of-the-art global air pollution forecasting model CAMS, our approach demonstrates superiority in 63% variables across all forecast time steps and 85% variables in predictions exceeding 48 hours. This work pioneers experimental validation of the effectiveness of meteorological fields in DL-based global air pollution forecasting, demonstrating that offline coupling meteorological fields with pollutants can achieve a 15% relative reduction in RMSE across all pollution variables. The research establishes a new paradigm for real-time global air pollution warning systems and delivers critical technical support for developing more efficient and comprehensive AI-powered global atmospheric forecasting frameworks.

Artificial Text Detection (ATD) is becoming increasingly important with the rise of advanced Large Language Models (LLMs). Despite numerous efforts, no single algorithm performs consistently well across different types of unseen text or guarantees effective generalization to new LLMs. Interpretability plays a crucial role in achieving this goal. In this study, we enhance ATD interpretability by using Sparse Autoencoders (SAE) to extract features from Gemma-2-2b residual stream. We identify both interpretable and efficient features, analyzing their semantics and relevance through domain- and model-specific statistics, a steering approach, and manual or LLM-based interpretation. Our methods offer valuable insights into how texts from various models differ from human-written content. We show that modern LLMs have a distinct writing style, especially in information-dense domains, even though they can produce human-like outputs with personalized prompts.