Is the war entering a new phase? 'New level of danger': Drone incidents scare Europe amid Russia-Ukraine war A quadcopter drone with plastic explosives attached to it flew unnoticed past air defence installations at Germany's Leipzig/Halle Airport, a key NATO airlift hub, on August 4. The drone hit a Ukrainian cargo plane but failed to detonate. It fell onto the tarmac and was found four hours later by a bus driver who stepped on it and called security, German media reported. DNA traces linked the drone to a firebomb that was mailed to the same airport and set a freight container on fire in July 2024, the Bild tabloid reported.

Is the war entering a new phase? Germany warns of'daily hybrid warfare' after explosive-laden drone found Germany is facing daily "hybrid warfare" attacks from abroad, an official has said, days after an explosive-laden drone was discovered at Leipzig/Halle Airport. Interior Minister Alexander Dobrindt told the local newspaper Bild am Sonntag on Sunday that foreign powers wanted to subdue Germany politically and socially by stirring up fear. "Espionage, sabotage, cyberattacks, or covert operations by foreign powers aimed at destabilising Germany or inflicting direct harm are a constant reality." He did not identify any countries behind the alleged attacks.

Is the war entering a new phase? A drone has exploded in Bulgaria near the Trans-Balkan gas pipeline, the latest in a surge of unidentified unmanned aerial vehicles entering European territory as regional tensions escalate due to Russia's ongoing war in Ukraine. Bulgarian Prime Minister Rumen Radev said on Saturday the drone exploded near the Romanian border and the gas pipeline, which links Turkiye to Ukraine. "There were no casualties," Radev added. Separately, a spokesperson for Germany's armed forces said on Saturday that two drones were spotted at about 10pm (20:00 GMT) on Thursday at a military base in Mechernich in the state of North Rhine-Westphalia, some 35km (22 miles) from the Belgian border.

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America's pettiest cyclist takes infuriating'revenge' on innocent drivers after spotting truck blocking Boston bike lane Royal fans criticise Oprah for failing to'challenge' Meghan and Harry's claims in tell-all 2021 interview - as she defends asking the duchess if she was'silenced' I caught my wife doing something so revolting in the shower. I don't believe her excuse for a second: DEAR JANE Over-the-counter allergy medication recalled over fears of contamination with drug that can cause'life-threatening' reactions Inside America's saddest ever murder trial: Lindsay Clancy strangled all three of her children... then got paralyzed as she tried to kill herself. Matt Damon reveals why he had a FEMALE stunt double in The Odyssey... amid backlash over'woke' casting World's most narcissistic countries revealed... and America's shock ranking ChatGPT maker OpenAI says AI model went rogue during testing and'escaped' into the internet where it launched'unprecedented' cyberattack I was hiding the shame of being a hard-working mother who drank and took cocaine. Then I took Mounjaro to lose weight... the effect on my humiliating habits was astonishing Nearly three dozen buildings revealed as potential sources of deadly lung disease outbreak... as deaths and cases continue to rise I thought I had the perfect marriage. Then my husband of 20 years revealed he'd been sleeping with men for a decade.

The French decision to use its own AI models comes amid growing concern among European governments about US-controlled technology. The French decision to use its own AI models comes amid growing concern among European governments about US-controlled technology. Move to ChapsVision is to avoid'strategic dependencies', says PM amid concern about reliance on US-controlled tools Tue 16 Jun 2026 13.08 EDTLast modified on Tue 16 Jun 2026 15.39 EDT France's domestic intelligence service is to ditch AI data tools from the US tech company Palantir in favour of a domestic provider in an effort to avoid "strategic dependency", the prime minister, Sébastien Lecornu, has said. "We must use our own AI models; we cannot accept new strategic dependencies in the digital sphere," Lecornu posted on social media. "We cannot rely on tools developed by foreign powers. France must have its own tools."

We propose a Koopman-enhanced physics-informed neural network (K--PINN) framework for parameter inference and forecasting in nonlinear epidemic models. This method combines Koopman operator theory and physics-informed learning. It maps epidemic states into a latent observable space where the dynamics evolve approximately linearly while satisfying the governing epidemic equations through automatic differentiation. This integration improves interpretability, parameter identifiability, and long-term predictive stability. We apply the proposed framework to a normalized SEIRSD epidemic model and evaluate it using synthetic monkeypox (Mpox) data and real-world datasets from Germany, Morocco, and Sweden for the SARS-CoV-2 virus. Synthetic trajectories are generated using a structure-preserving, nonstandard finite difference scheme to ensure reliable training data. Numerical results demonstrate that K--PINN achieves more accurate parameter estimation, trajectory reconstruction, and long-term forecasting than classical PINNs and Koopman-EDMD approaches. These results suggest that K--PINN is an effective machine learning framework for epidemic modeling that can be extended to more complex systems.

Evaluating the open-form textual responses generated by Large Language Models (LLMs) typically requires measuring the semantic similarity of the response to a (human generated) reference. However, there is evidence that current semantic similarity methods may capture syntactic or lexical forms over semantic content. While benchmarks exist for semantic equivalence, they often suffer from high generation costs due to reliance on subjective human judgment, limited availability for domain-specific applications, and unclear definitions of equivalence. This paper introduces a novel method for generating benchmarks to evaluate semantic similarity methods for LLM outputs, specifically addressing these limitations. Our approach leverages knowledge graphs (KGs) to generate pairs of naturallanguage statements that are semantically similar or dissimilar, with dissimilar pairs categorized into one of four sub-types. We generate benchmark datasets in four different domains (general knowledge, biomedicine, finance, biology), and conduct a comparative study of semantic similarity methods including traditional natural language processing scores and LLM-as-a-judge predictions. We observe that the sub-type of semantic variation, as well as the domain of the benchmark impact the performance of semantic similarity methods, with no method being consistently superior.

Evaluating the open-form textual responses generated by Large Language Models (LLMs) typically requires measuring the semantic similarity of the response to a (human generated) reference. However, there is evidence that current semantic similarity methods may capture syntactic or lexical forms over semantic content. While benchmarks exist for semantic equivalence, they often suffer from high generation costs due to reliance on subjective human judgment, limited availability for domain-specific applications, and unclear definitions of equivalence. This paper introduces a novel method for generating benchmarks to evaluate semantic similarity methods for LLM outputs, specifically addressing these limitations. Our approach leverages knowledge graphs (KGs) to generate pairs of naturallanguage statements that are semantically similar or dissimilar, with dissimilar pairs categorized into one of four sub-types. We generate benchmark datasets in four different domains (general knowledge, biomedicine, finance, biology), and conduct a comparative study of semantic similarity methods including traditional natural language processing scores and LLM-as-a-judge predictions. We observe that the sub-type of semantic variation, as well as the domain of the benchmark impact the performance of semantic similarity methods, with no method being consistently superior.

An escaped tiger believed to be owned by Germany's Tiger Queen has been shot dead by police after attacking one of its keepers, according to local media reports. Police say a 73-year-old man was seriously injured after being attacked on Sunday while he was inside the animal's enclosure, located in a privately-owned facility on the outskirts of the German city of Leipzig. The tiger escaped the enclosure and was found shortly after by armed police, who shot and killed the animal. The site of the enclosure is believed to be owned by controversial trainer and private owner Carmen Zander, who describes herself as Germany's Tiger Queen. The animal was one of eight big cats kept at the industrial site near the German town of Schkeuditz, according to local media.