Anti-Trump Protesters Take Aim at'Naive' US-UK AI Deal Thousands marched in London to protest President Donald Trump's second state visit. Among them were many environmental activists unhappy with Britain's new AI deal with the US. They played extremely loud music. They let off foul-smelling smoke from a can. Thousands of people gathered on Wednesday in central London to protest against Trump's presence in the UK, accusing the UK government of kowtowing to him by hosting him for a state visit for the second time.

A wave of AI users presenting in states of psychological distress gave birth to an unofficial diagnostic label. Experts say it's neither accurate nor needed, but concede that it's likely to stay. A new trend is emerging in psychiatric hospitals. People in crisis are arriving with false, sometimes dangerous beliefs, grandiose delusions, and paranoid thoughts. A common thread connects them: marathon conversations with AI chatbots.

How is Russia replenishing its military? What is a'coalition of the willing'? How China forgot promises and'debts' to Ukraine How are Europe, the US pulling apart on Ukraine? A Ukrainian drone has struck a car in Russia's Belgorod border region, killing one person and injuring another, according to the region's governor. The Ukrainian army lost more than 1,500 troops during front-line fighting over the past day, reported Russia's state TASS news agency, citing the Ministry of Defence.

Misinformation in healthcare, from vaccine hesitancy to unproven treatments, poses risks to public health and trust in medical systems. While machine learning and natural language processing have advanced automated fact-checking, validating biomedical claims remains uniquely challenging due to complex terminology, the need for domain expertise, and the critical importance of grounding in scientific evidence. We introduce CER (Combining Evidence and Reasoning), a novel framework for biomedical fact-checking that integrates scientific evidence retrieval, reasoning via large language models, and supervised veracity prediction. By integrating the text-generation capabilities of large language models with advanced retrieval techniques for high-quality biomedical scientific evidence, CER effectively mitigates the risk of hallucinations, ensuring that generated outputs are grounded in verifiable, evidence-based sources. Evaluations on expert-annotated datasets (HealthFC, BioASQ-7b, SciFact) demonstrate state-of-the-art performance and promising cross-dataset generalization. Code and data are released for transparency and reproducibility: https://github.com/PRAISELab-PicusLab/CER

Anatomical trees play an important role in clinical diagnosis and treatment planning. Yet, accurately representing these structures poses significant challenges owing to their intricate and varied topology and geometry. Most existing methods to synthesize vasculature are rule based, and despite providing some degree of control and variation in the structures produced, they fail to capture the diversity and complexity of actual anatomical data. We developed a Recursive variational Neural Network (RvNN) that fully exploits the hierarchical organization of the vessel and learns a low-dimensional manifold encoding branch connectivity along with geometry features describing the target surface. After training, the RvNN latent space can be sampled to generate new vessel geometries. By leveraging the power of generative neural networks, we generate 3D models of blood vessels that are both accurate and diverse, which is crucial for medical and surgical training, hemodynamic simulations, and many other purposes. These results closely resemble real data, achieving high similarity in vessel radii, length, and tortuosity across various datasets, including those with aneurysms. To the best of our knowledge, this work is the first to utilize this technique for synthesizing blood vessels.

Institute of Mathematics and Statistics, Federal University of Rio Grande do Sul (UFRGS), Av. Center for Coastal and Oceanic Geology Studies (CECO), Federal University of Rio Grande do Sul (UFRGS), Av. Abstract The forecast of wave variables are important for several applications that depend on a better description of the ocean state. Due to the chaotic behaviour of the differential equations which model this problem, a well know strategy to overcome the difficulties is basically to run several simulations, by for instance, varying the initial condition, and averaging the result of each of these, creating an ensemble. Moreover, in the last few years, considering the amount of available data and the computational power increase, machine learning algorithms have been applied as surrogate to traditional numerical models, yielding comparative or better results. In this work, we present a methodology to create an ensemble of different artificial neural networks architectures, namely, MLP, RNN, LSTM, CNN and a hybrid CNN-LSTM, which aims to predict significant wave height on six different locations in the Brazilian coast. The networks are trained using NOAA's numerical reforecast data and target the residual between observational data and the numerical model output. A new strategy to create the training and target datasets is demonstrated. Introduction Numerical simulations of both weather and ocean parameters rely on the evolution of nonlinear dynamical systems that have a high sensitivity on initial conditions. Considering that errors in the observations and analysis are present, and therefore in the initial conditions, the concept of a unique deterministic solution of the governing equations becomes fragile [1, 2].

The state banquet is the spectacular showstopper of a state visit, a glittering feast with speeches, royal toasts, trumpet fanfares and fancy food and wine. It's diplomacy served up with fine dining. A cut-glass shock-and-awe approach to hospitality designed to make a visiting leader like President Trump feel special. The setting in St George's Hall inside Windsor Castle is a remarkable sight, a mix of medieval banquet and Harry Potter film. Elaborately uniformed staff around the hall are as drilled as the soldiers who have been on parade during the day.

Feedback was amazed to hear that dog ownership could cause a hurricane across the other side of the world. Or are we barking up the wrong tree? Kristian Steensen Nielsen seems like a sensible type. A researcher at the Copenhagen Business School in Denmark, he studies "the role of behavior change in mitigating climate change and conserving biodiversity". In other words, how can we make our lives more environmentally friendly, and how and when do those changes scale up to become truly effective?

BirdCast can help you follow their fall migration. Breakthroughs, discoveries, and DIY tips sent every weekday. Open up the weather radar and you might see what looks like precipitation when it's not raining at all. Those bright green spots are often birds during their annual fall migration -and you can follow along. According to BirdCast, 262 million birds are predicted to hit the skies tonight alone.

Bird photos that really take flight. Breakthroughs, discoveries, and DIY tips sent every weekday. An estimated 50 billion wild birds populate our planet, according to a 2021 study . From garbage-eating urban pigeons to colorful parrots in tropical forests, the diversity of birds is impressive. For the past 120 years, the National Audubon Society has worked to helped Earth's birds through conservation and awareness campaigns.