Drone detection technology has led to an increase in airborne smuggling operations over U.S. prisons, putting authorities in a tough spot as federal regulations prevent drones from being brought down.

Can the US legally seize a Venezuelan tanker? What are the implications of Trump's Somali'garbage' comments? United States President Donald Trump has often said that since he took office in January, the US has received trillions of dollars in promises of investments, and the dollar amount he cites changes. On his second day in office, January 21, Trump said the US had "already secured nearly $3 trillion of new investments". By May 8, that figure had risen to " close to $10 trillion ".

An arena warrior on a losing streak takes refuge in a vast forest where she discovers the joy of working in a cosy teashop. From this simple premise comes a joyful game of mindfulness and social interaction, as Alta learns how to serve up witty conversation and decent hot drinks. Colourful and highly stylised, it is a thoughtful study of burnout and recovery. An attempted-murder mystery set in an a 1920s all-girls private school reveals itself to also be an eviscerating takedown of British class politics. Witty and beautifully drawn, it is full of amusing boarding-school stereotypes, from self-interested prefects to a terrifying matron, whose motivations and personal grievances must be slowly unpicked.

The widespread adoption of Artificial Intelligence (AI) is likely to displace people from jobs in a similar way seen during the Industrial Revolution, the governor of the Bank of England has said. Andrew Bailey said the UK needed to have the training, education, [and] skills in place so workers could shift into jobs that use AI. He told the BBC Radio 4's Today programme people looking for a job would find securing employment a lot easier if they had such skills. However, he warned that there was an issue with younger, inexperienced professionals finding it difficult to secure entry-level roles due to AI. We do have to think about, what is it doing to the pipeline of people?

Revealed: Chilling text NASCAR star Greg Biffle's wife sent to her mom just minutes before tragic plane crash'Old age' doesn't kill us... scientists reveal true causes of death Immutable: I can't get enough of Melania, the Real Housewife of Washington, says JAN MOIR The tiny diet change that brought down my sky-high cholesterol WITHOUT statins or drugs. Mike was told he risked a heart attack or stroke. CNBC anchor who slammed Trump's tariffs as'insane' stunned live on air as inflation figures send shockwaves through Wall Street Dramatic bodycam video shows moment suspected kidnapper is arrested after 40 years on the run... as her neighbor thinks arrest is a joke Rob Reiner's'petrified' parting words about son Nick at Conan O'Brien party... and why his haunted A-list friends can't stop talking about it Reiner family bombshell as insiders reveal who is paying for Nick's celebrity lawyer... their secret motive... and who will REALLY inherit $200m fortune Doctors said my hip pain was just tendinitis from sitting all day at work. The real cause may kill me... they had left it far too late Bondi hero is handed $2.5million cheque in his hospital bed - as hero asks unbelievable question Pete Davidson is a dad! Kim Kardashian's ex welcomes first child with model girlfriend Elsie Hewitt Mica Miller's pastor husband is indicted for shocking acts before his wife was killed days after filing for divorce Transportation Secretary Sean Duffy's daughter slams TSA as'unconstitutional' after she was subjected to a pat down for refusing to go through the body scanner Jeffrey Epstein attended dinner with tech billionaires three years after he was convicted of sex crimes - as new photos of the event are released from pedophile's estate Terrifying maps break down exactly who is at risk of new'super flu' exploding across America... as doctors reveal symptoms to really worry about READ MORE: Blind psychic Baba Vanga's world-changing 2025 prophecy feared to occur in just DAYS A blind psychic, who allegedly foretold 9/11 and the Covid pandemic, shared several world-changing prophecies for 2026 before her death nearly 30 years ago. Baba Vanga was a Bulgarian mystic and clairvoyant who became a cult figure among conspiracy theorists after several of her eerie pronouncements were proved true.

What is in the 28-point US plan for Ukraine? 'Ukraine is running out of men, money and time' Can the US get all sides to end the war? Why is Europe opposing Trump's peace plan? Three people, including two crew members of a cargo vessel, were killed in overnight Ukrainian drone attacks on the Russian port of Rostov-on-Don and the town of Bataysk in the country's southern Rostov region, local governor Yury Slyusar said. Russian strikes near Ukraine's Black Sea port of Odesa killed a woman in her car and hit infrastructure.

Modern generative models hold great promise for accelerating diverse tasks involving the simulation of physical systems, but they must be adapted to the specific constraints of each domain. Significant progress has been made for biomolecules and crystalline materials. Here, we address amorphous materials (glasses), which are disordered particle systems lacking atomic periodicity. Sampling equilibrium configurations of glass-forming materials is a notoriously slow and difficult task. This obstacle could be overcome by developing a generative framework capable of producing equilibrium configurations with well-defined likelihoods. In this work, we address this challenge by leveraging an equivari-ant Riemannian stochastic interpolation framework which combines Riemannian stochastic interpolant and equivariant flow matching. Our method rigorously incorporates periodic boundary conditions and the symmetries of multi-component particle systems, adapting an equivariant graph neural network to operate directly on the torus. Our numerical experiments on model amorphous systems demonstrate that enforcing geometric and symmetry constraints significantly improves generative performance.

Survival analysis encompasses a broad range of methods for analyzing time-to-event data, with one key objective being the comparison of survival curves across groups. Traditional approaches for identifying clusters of survival curves often rely on computationally intensive bootstrap techniques to approximate the null hypothesis distribution. While effective, these methods impose significant computational burdens. In this work, we propose a novel approach that leverages the k-means and log-rank test to efficiently identify and cluster survival curves. Our method eliminates the need for computationally expensive resampling, significantly reducing processing time while maintaining statistical reliability. By systematically evaluating survival curves and determining optimal clusters, the proposed method ensures a practical and scalable alternative for large-scale survival data analysis. Through simulation studies, we demonstrate that our approach achieves results comparable to existing bootstrap-based clustering methods while dramatically improving computational efficiency. These findings suggest that the log-rank-based clustering procedure offers a viable and time-efficient solution for researchers working with multiple survival curves in medical and epidemiological studies.

Streamflow forecasting is crucial for water resource management and risk mitigation. While deep learning models have achieved strong predictive performance, they often overlook underlying physical processes, limiting interpretability and generalization. Recent causal learning approaches address these issues by integrating domain knowledge, yet they typically rely on fixed causal graphs that fail to adapt to data. We propose CauStream, a unified framework for causal spatiotemporal streamflow forecasting. CauSTream jointly learns (i) a runoff causal graph among meteorological forcings and (ii) a routing graph capturing dynamic dependencies across stations. We further establish identifiability conditions for these causal structures under a nonparametric setting. We evaluate CauSTream on three major U.S. river basins across three forecasting horizons. The model consistently outperforms prior state-of-the-art methods, with performance gaps widening at longer forecast windows, indicating stronger generalization to unseen conditions. Beyond forecasting, CauSTream also learns causal graphs that capture relationships among hydrological factors and stations. The inferred structures align closely with established domain knowledge, offering interpretable insights into watershed dynamics. CauSTream offers a principled foundation for causal spatiotemporal modeling, with the potential to extend to a wide range of scientific and environmental applications.

Instacart settles Federal Trade Commission's claim it deceived US shoppers Instacart has agreed to pay $60m in refunds to settle allegations brought by the United States Federal Trade Commission (FTC) that the online grocery delivery platform deceived consumers about its membership programme and free delivery offers. According to court documents filed in San Francisco on Thursday, Instacart's offer of "free delivery" for first orders was illusory because shoppers were charged other fees, the FTC alleged. "The FTC is focused on monitoring online delivery services to ensure that competitors are transparently competing on price and delivery terms," said Christopher Mufarrige, who leads the FTC's consumer protection work. An Instacart spokesperson said the company flatly denies any allegations of wrongdoing, but that the settlement allows the company to focus on shoppers and retailers. "We provide straightforward marketing, transparent pricing and fees, clear terms, easy cancellation, and generous refund policies -- all in full compliance with the law and exceeding industry norms," the spokesperson said.