US assembles the most aerial firepower since Iraq War as Trump prepares to strike Iran'in just DAYS'... and president is'choosing between two devastating options of attack' Model agency boss who'scouted' victims for Epstein was secretly planning to testify against him... only to suddenly change his mind before meeting chillingly similar fate to notorious pedophile The monarchy has survived wars and countless crises... but this is why it may not survive Andrew's arrest - and why the rift at the heart of the family is about to get so much worse: ROBERT JOBSON But countless women (and some husbands) are secretly getting it for thrilling sex side effects... risking a truly putrid complication FBI'has names and photos of people who may be masked suspect caught on surveillance video outside Nancy Guthrie's home' Widower whose wife set herself on fire after alleged affair with married congressman finally breaks silence to reveal their texts... and heartbreaking video of her death The side-effects were unbearable and I swore off the drug forever. This is the simple diet that helped me shed the pounds... and I'm not alone. Lindsey Vonn shares nervous post as she awaits fifth surgery on broken leg after Olympic fall and dog's death Jason Bateman says he quit cocaine and alcohol to ease'tension' in his marriage Humiliating real reason Mia Goth left Shia LaBeouf: What'friends and lovers' are all saying behind his back... after Mardi Gras brawl Turmoil ramps up at Today Show as Hoda ditches her'family first' exit to reclaim her coveted anchor seat.... whether Savannah returns or not Whereabouts of Andrew's ex-wife and daughters remain unknown as former prince is arrested over public misconduct claims Peter Greene's cause of death revealed two months after Pulp Fiction star was found dead at 60 in NYC apartment Tucker Carlson'DETAINED' in Israel: Journalist'dragged into interrogation room' as explosive interview sparks diplomatic firestorm My teenage son picked up a dirty habit to'look cool' in front of his friends. He was rushed to hospital with deadly lung condition now I'm issuing an urgent plea What happens now Andrew Mountbatten-Windsor has been arrested? Germany's army chief warns Europe will suffer'things we cannot even imagine right now' as Putin looks to go to war with Europe - and slams'egomaniac' Trump Scientists confirm wet weather slashes life satisfaction by 6% - as soggy Brits vent they're'flipping sick of it' READ MORE: You think this is bad?

Correlation mechanism to capture cross-time dependency for forecasting. Besides, the dimension of the channel is set to 16 based on efficiency considerations. Weather, and the look-back window size is set as 96. Proposition 2. The time and space complexity for the Cross-variable GNN is Frequency enhanced decomposed transformer for long-term series forecasting.

After days and weeks of gloomy skies and relentless rain for some, there has finally been a change to our weather in the United Kingdom. Arctic air across the UK means the weekend starts cold and frosty with some snow and ice, especially in northern parts. But, there will be lots of sunshine for most throughout Saturday. However, it will be temporary as rain with more snow and ice spreads overnight into Sunday. Further Met Office yellow warnings for ice and snow have been issued across Scotland and northern England from 21:00 GMT to 10:00 on Sunday.

You would be forgiven for thinking the rain this year has been relentless - because in some parts of the UK, it actually has been. Here at BBC Weather we have been watching computer models closely for signs of when that pattern will change. These computer-generated forecasts go out about two weeks into the future - and models have often been hinting at a change to colder and drier weather on that timescale. However, they have then reverted to the familiar wet pattern as we have got closer to the time. Now though, there are stronger signals of a change for some of us - albeit perhaps only a temporary one.

Why do your joints hurt when it's cold? And what you can do to ease the aches. Winter can amplify aches and pains through pressure shifts, reduced movement, and muscle tightening. Breakthroughs, discoveries, and DIY tips sent six days a week. Each winter, over a million "snowbirds" descend on places like Florida and Arizona to avoid the season's freezing temperatures and instead, ride it out in warmth.

The BBC's director general is to leave the broadcaster in April, five months after he announced his resignation amid a storm about the way Panorama edited a Donald Trump speech. Tim Davie stayed in his post after announcing his resignation in November, but will depart on 2 April. He will be replaced by an interim DG, Rhodri Talfan Davies, who has been director of nations since 2021 and is currently leading the BBC's work on generative AI. The search is under way for a permanent director general, one of the most demanding jobs in the British media. Davie has been responsible for dealing with a series of scandals and crises since becoming the BBC's 17th director general in 2020.

In an era marked by the rapid scaling of foundation models, autonomous driving technologies are approaching a transformative threshold where end-to-end autonomous driving (E2E-AD) emerges due to its potential of scaling up in the data-driven manner. However, existing E2E-AD methods are mostly evaluated under the open-loop log-replay manner with L2 errors and collision rate as metrics (e.g., in nuScenes), which could not fully reflect the driving performance of algorithms as recently acknowledged in the community. For those E2E-AD methods evaluated under the closed-loop protocol, they are tested in fixed routes (e.g., Town05Long and Longest6 in CARLA) with the driving score as metrics, which is known for high variance due to the unsmoothed metric function and large randomness in the long route. Besides, these methods usually collect their own data for training, which makes algorithm-level fair comparison infeasible. To fulfill the paramount need of comprehensive, realistic, and fair testing environments for Full Self-Driving (FSD), we present Bench2Drive, the first benchmark for evaluating E2E-AD systems' multiple abilities in a closed-loop manner. Bench2Drive's official training data consists of 2 million fully annotated frames, collected from 10000 short clips uniformly distributed under 44 interactive scenarios (cut-in, overtaking, detour, etc), 23 weathers (sunny, foggy, rainy, etc), and 12 towns (urban, village, university, etc) in CARLA v2. Its evaluation protocol requires E2E-AD models to pass 44 interactive scenarios under different locations and weathers which sums up to 220 routes and thus provides a comprehensive and disentangled assessment about their driving capability under different situations. We implement state-of-the-art E2E-AD models and evaluate them in Bench2Drive, providing insights regarding current status and future directions.

The Massachusetts Bay Transportation Authority (MBTA) is the main public transit provider in Boston, operating multiple means of transport, including trains, subways, and buses. However, the system often faces delays and fluctuations in ridership volume, which negatively affect efficiency and passenger satisfaction. To further understand this phenomenon, this paper compares the performance of existing and unique methods to determine the best approach in predicting gated station entries in the subway system (a proxy for subway usage) and the number of delays in the overall MBTA system. To do so, this research considers factors that tend to affect public transportation, such as day of week, season, pressure, wind speed, average temperature, and precipitation. This paper evaluates the performance of 10 statistical and machine learning models on predicting next-day subway usage. On predicting delay count, the number of models is extended to 11 per day by introducing a self-exciting point process model, representing a unique application of a point-process framework for MBTA delay modeling. This research involves experimenting with the selective inclusion of features to determine feature importance, testing model accuracy via Root Mean Squared Error (RMSE). Remarkably, it is found that providing either day of week or season data has a more substantial benefit to predictive accuracy compared to weather data; in fact, providing weather data generally worsens performance, suggesting a tendency of models to overfit.

What does'chance of precipitation' really mean? Here's how to figure out if you can leave the umbrella at home. It's not always "when it rains, it pours." Breakthroughs, discoveries, and DIY tips sent every weekday. Understanding the weather forecast can sometimes feel like reading tea leaves.

Long-horizon multivariate time-series forecasting is challenging because realistic predictions must (i) denoise heterogeneous signals, (ii) track time-varying cross-series dependencies, and (iii) remain stable and physically plausible over long rollout horizons. We present PRISM, which couples a score-based diffusion preconditioner with a dynamic, correlation-thresholded graph encoder and a forecast head regularized by generic physics penalties. We prove contraction of the induced horizon dynamics under mild conditions and derive Lipschitz bounds for graph blocks, explaining the model's robustness. On six standard benchmarks , PRISM achieves consistent SOTA with strong MSE and MAE gains.