Will Gulf states join war? What is the UAE's Barakah nuclear plant, nearly hit by a drone? A drone attack that caused a fire close to the Barakah Nuclear Energy Plant in the United Arab Emirates has raised further concerns about nuclear security and military escalation in the Gulf as discussions of peace between Iran and the United States hang in the balance. Barakah was the first nuclear power station to be built on the Arabian Peninsula. What is the Barakah Nuclear Energy Plant? Barakah is a nuclear energy plant located in Al Dhafra, the largest municipal region of the emirate of Abu Dhabi.

Musk v. Altman week 3: Musk and Altman traded blows over each other's credibility. Now the jury will pick a side. In the final week of the Musk v. Altman trial, lawyers attacked the credibility of the two tech leaders. Sam Altman was accused of lying and self-dealing, while Elon Musk was portrayed as a power-seeker trying to control artificial general intelligence. The case unearthed new details about the two arch-rivals and OpenAI's contested nonprofit status, as well as a golden trophy of a donkey's ass awarded to an employee who challenged Musk. Michelle Kim, who's also a lawyer, has been in court throughout the Musk v. Altman trial.

Could the war trigger a hunger crisis? How well do you know Iran? This video may contain light patterns or images that could trigger seizures or cause discomfort for people with visual sensitivities. US President Donald Trump warns Iran that the "clock is ticking" for a peace deal to be reached with Washington. Saudi Arabia says it intercepted three drones, as the UAE reported a separate drone strike near its Barakah nuclear power plant that sparked a fire.

Score-based generative models are trained in high-dimensional ambient spaces, yet many data distributions are supported on low-dimensional nonlinear structures. We prove that, for compact $d$-dimensional smooth manifolds $\mathcal{M} \subset [0,1]^D$ with $d > 2$ and $β$-Hölder densities strictly positive on $\mathcal{M}$, a variance-preserving SGM estimator attains the intrinsic Wasserstein--1 sample exponent $\tilde{\mathcal{O}}(D^{\mathcal{O}_β(d)}n^{-(β+1)/(d+2β)})$, up to logarithmic factors and explicit geometry and density factors. The full nonasymptotic bound explicitly isolates the finite-order geometry envelope, Hölder radius, density lower bound, ambient dependence, and finite-order correction terms. The analysis separates score approximation into a large-noise tangent-cell regime and a small-noise projection-centered, de-Gaussianized Laplace regime. The key technical ingredient is a ReLU implementation of nearest-projection coordinates via finite intrinsic anchors and Gauss--Newton iterations, rather than approximating the manifold projection as a black-box high-dimensional smooth map. Consequently, for families with polynomially controlled geometry and density lower bounds, the constructed score-network parameters have polynomial ambient dependence.

The United Arab Emirates is investigating the source of a drone strike which triggered a fire near a nuclear power station, officials have said. The country's defence ministry said three drones had entered the UAE from the western border direction on Sunday. While two were intercepted, the third drone struck an electrical generator outside the inner perimeter of the Barakah Nuclear Power Plant in Abu Dhabi. No injuries were reported and there was no impact on radiological safety levels, local authorities said. The country's defence ministry said in a statement that investigations were under way to determine the source of the attacks.

Could the war trigger a hunger crisis? How well do you know Iran? Drone strike sparks fire on perimeter of UAE's Barakah nuclear power plant A drone strike has sparked a fire on the perimeter of the Barakah Nuclear Energy Plant in the United Arab Emirates (UAE), raising new concerns over a potential new regional escalation amid a fragile ceasefire between Iran and the United States. Authorities in Abu Dhabi said the blaze broke out at an electrical generator outside the plant's inner perimeter in the Al Dhafra region on Sunday. No injuries were reported, and officials said radiation levels remained normal.

Charlie Berens: 'I will stick to comedy when our politicians stick to policy and stop protecting big tech and start protecting the people that put them into office.' Charlie Berens: 'I will stick to comedy when our politicians stick to policy and stop protecting big tech and start protecting the people that put them into office.' 'Nobody's negotiating for the people here': comedian Charlie Berens takes on AI datacenters Known for his'Manitowoc Minute' skits and midwestern humor, the journalist turned comedian is speaking out against the AI datacenter boom in Wisconsin Last summer, journalist turned comedian Charlie Berens started getting social media messages from concerned Wisconsin residents about plans for a massive datacenter campus in their state. The developer, Vantage Data Centers, claimed the $8 bn project would largely run on zero-emission energy resources like solar, wind and battery storage. The company said the campus would bring thousands of temporary construction jobs and potentially more than 1,000 permanent jobs to Port Washington, a city of 13,000 people about a half-hour north of Milwaukee. Residents opposed the project for what they said was lack of transparency and criticized the lucrative tax incentives offered to Vantage.

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Ford and GM are backing away from electric vehicles and moving into the battery storage business. And it all comes back to AI. Automakers make cars--it's in the name. But lately, politics, current events, and Wall Street's latest preoccupation, artificial intelligence, have them looking a lot more like energy companies. The pivot, analysts say, could give US auto manufacturers struggling through a transition to electric vehicles an easier path over the next few years. Whether it works will come down to the same technology that automakers once promised would power the majority of their lineups: batteries .

Physics-informed neural networks (PINNs) provide a mesh-free framework for solving PDE-constrained inverse problems, but their extension to Bayesian inversion still faces a fundamental difficulty: prior distributions are typically defined in the weight space of neural networks, whereas physically meaningful prior assumptions are more naturally expressed in function space. In this study, we introduce a unified framework, termed functional-prior-based approaches to Bayesian PDE-constrained inversion using physics-informed neural networks (fpBPINN), to incorporate functional priors into Bayesian PINN-based inversion. We consider two complementary approaches. The first is a functional-prior-informed Bayesian PINN (FPI-BPINN), in which a neural network weight prior is learned to be consistent with a prescribed functional prior, and Bayesian inference is subsequently performed in weight space. The second is function-space particle-based variational inference for PINNs (fParVI-PINN), which performs Bayesian estimation using ParVI directly in function space. We also show that random Fourier features (RFF) play an important role in representing Gaussian functional priors with neural networks and in improving posterior approximation. We applied the proposed approaches to one-dimensional seismic traveltime tomography and two-dimensional Darcy-flow permeability inversion. These numerical experiments showed that both approaches accurately estimated posterior distributions, highlighting the significance of introducing physically interpretable functional priors into Bayesian PINN-based inverse problems. We also identified the contrasting advantages of FPI-BPINN and fParVI-PINN, namely flexibility and accuracy, respectively.