Russian authorities have returned the remains of 1,000 Ukrainian soldiers, Ukraine's Coordination Headquarters for the Treatment of Prisoners of War said on Monday, according to The Kyiv Independent news outlet. Russia's state-run TASS news agency confirmed that Russia returned the bodies of 1,000 soldiers, adding that Ukraine returned the bodies of 19 Russian soldiers. Separately, TASS reported that about 1,370 Ukrainian soldiers were killed in a single day, citing the Russian Ministry of Defence. Al Jazeera could not verify this claim independently. Russian forces dropped 250kg (550 lbs) bombs on the city of Kostiantynivka in Ukraine's Donetsk region, Serhii Horbunov, the head of the Kostiantynivka City Military Administration, wrote on Facebook on Monday.

Ukrainian authorities said Russian attacks before the talks killed 14 people across the country. This includes a drone attack on an apartment building in Kharkiv that killed at least seven people. The victims on Monday also included three people who were killed in a ballistic missile strike on the southeastern city of Zaporizhzhia, the regional governor said, adding that another 23 were wounded. Ukraine's air force said Russia launched a total of four Iskander-M ballistic missiles and 140 Shahed and decoy drones across Ukraine overnight, of which 88 drones were shot down or jammed. In Russia, falling debris from a Ukrainian drone shot down by Russian forces set off fires in a hospital building and on the grounds of an oil refinery, south of the city of Volgograd, regional governor Andrei Bocharov said in a post on Telegram.

The rapid adoption of Large Language Models (LLMs) in unmanned systems has significantly enhanced the semantic understanding and autonomous task execution capabilities of Unmanned Aerial Vehicle (UAV) swarms. However, limited communication bandwidth and the need for high-frequency interactions pose severe challenges to semantic information transmission within the swarm. This paper explores the feasibility of LLM-driven UAV swarms for autonomous semantic compression communication, aiming to reduce communication load while preserving critical task semantics. To this end, we construct four types of 2D simulation scenarios with different levels of environmental complexity and design a communication-execution pipeline that integrates system prompts with task instruction prompts. On this basis, we systematically evaluate the semantic compression performance of nine mainstream LLMs in different scenarios and analyze their adaptability and stability through ablation studies on environmental complexity and swarm size. Experimental results demonstrate that LLM-based UAV swarms have the potential to achieve efficient collaborative communication under bandwidth-constrained and multi-hop link conditions.

As urban aerial mobility (UAM) infrastructure development accelerates globally, cities like Shenzhen are planning large-scale vertiport networks (e.g., 1,200+ facilities by 2026). Existing planning frameworks remain inadequate for this complexity due to historical limitations in data granularity and real-world applicability. This paper addresses these gaps by first proposing the Capacitated Dynamic Maximum Covering Location Problem (CDMCLP), a novel optimization framework that simultaneously models urban-scale spatial-temporal demand, heterogeneous user behaviors, and infrastructure capacity constraints. Building on this foundation, we introduce an Integrated Planning Recommendation System that combines CDMCLP with socio-economic factors and dynamic clustering initialization. This system leverages adaptive parameter tuning based on empirical user behavior to generate practical planning solutions. Validation in a Chinese center city demonstrates the effectiveness of the new optimization framework and recommendation system. Under the evaluation and optimization of CDMCLP, the quantitative performance of traditional location methods are exposed and can be improved by 38\%--52\%, while the recommendation system shows user-friendliness and the effective integration of complex elements. By integrating mathematical rigor with practical implementation considerations, this hybrid approach bridges the gap between theoretical location modeling and real-world UAM infrastructure planning, offering municipalities a pragmatic tool for vertiport network design.

The rapid advancement of Transformer-based models has reshaped the landscape of uncrewed aerial vehicle (UAV) systems by enhancing perception, decision-making, and autonomy. This review paper systematically categorizes and evaluates recent developments in Transformer architectures applied to UAVs, including attention mechanisms, CNN-Transformer hybrids, reinforcement learning Transformers, and large language models (LLMs). Unlike previous surveys, this work presents a unified taxonomy of Transformer-based UAV models, highlights emerging applications such as precision agriculture and autonomous navigation, and provides comparative analyses through structured tables and performance benchmarks. The paper also reviews key datasets, simulators, and evaluation metrics used in the field. Furthermore, it identifies existing gaps in the literature, outlines critical challenges in computational efficiency and real-time deployment, and offers future research directions. This comprehensive synthesis aims to guide researchers and practitioners in understanding and advancing Transformer-driven UAV technologies.

Fox News' Jacqui Heinrich reports the latest on Ukraine peace talks ahead of President Donald Trump's White House meeting. National security analyst Rebeccah Heinrichs also weighs in on the latest peace negotiations during'America's Newsroom.' Just as Ukrainian President Volodymyr Zelenskyy arrived in Washington, D.C. to meet President Donald Trump at the White House, Russia routed his nation with airstrikes on Monday, killing 10. Seven people, including a toddler and a 16-year-old, were killed by a Russian drone strike on the Ukrainian city of Kharkiv, according to local authorities. Ukrainian officials took the strikes as a message from Russian President Vladimir Putin that he has no intention to end the war.

Russian attacks on major Ukrainian cities have killed at least 12 people as President Volodymyr Zelenskyy visits Washington, DC, supported by European leaders, for high-stakes peace talks with United States President Donald Trump that could determine Ukraine's future and its fate in the war, now in its fourth year. An entire family, including a toddler and a 16-year-old, were among seven people killed in an overnight drone strike on a residential neighbourhood in the northeastern city of Kharkiv, authorities said on Monday. The attack also injured 20 people, including six children. Russian forces killed five people and injured four in attacks in eastern Ukraine's Donetsk region, where some of the fiercest fighting on the ground rages on and where Russian President Vladimir Putin, feeling Moscow has the upper hand, seeks Ukraine's withdrawal from the third of the region Kyiv still controls. In Zaporizhzhia, a city in the southeast, 17 people were injured in an attack, according to Governor Ivan Fedorov.

To counter an imminent multi-drone attack on a city, defenders have deployed drones across the city. These drones must intercept/eliminate the threat, thus reducing potential damage from the attack. We model this as a Sequential Stackelberg Security Game, where the defender first commits to a mixed sequential defense strategy, and the attacker then best responds. We develop an efficient algorithm called S2D2, which outputs a defense strategy. We demonstrate the efficacy of S2D2 in extensive experiments on data from 80 real cities, improving the performance of the defender in comparison to greedy heuristics based on prior works. We prove that under some reasonable assumptions about the city structure, S2D2 outputs an approximate Strong Stackelberg Equilibrium (SSE) with a convenient structure. Introduction There has been a lot of recent concern about multi-drone attacks [1, 2, 3, 4, 5, 6, 7, 8], especially in highly populated urban areas where not all countermeasures can be ...

Fox News senior White House correspondent Peter Doocy reports on Russian President Vladimir Putin's latest demands in negotiations to end the Russia-Ukraine war on'Fox Report.' A Ukrainian sniper unit on Thursday reportedly broke the world record for the longest confirmed sniper kill, eliminating Russian troops from a distance of more than 13,000 feet (4,000 meters). The shot, fired by a Ukrainian-produced rifle and aided by artificial intelligence and drone guidance, left two Russian soldiers dead in the area of Pokrovsk, Ukraine, the Kyiv Post reported. "The record-breaking shot was made on Aug. 14, 2025, using artificial intelligence under the guidance of [an unmanned aerial vehicle] complex with a 14.5 mm alligator rifle," said military journalist Yuri Butusov, according to the Kyiv Post. A serviceman of the 152nd Separate Jaeger Brigade of the Ukrainian Armed Forces checks the sky for Russian combat drones amid Russia's attack on Ukraine near the town of Pokrovsk in Donetsk region, Ukraine, Aug. 5, 2025.

Russia has made gains in Ukraine's Donetsk region before President Vladimir Putin's high-stakes meeting with his United States counterpart Donald Trump in Alaska, raising fears that it may have increased its leverage amid talks aimed at ending the war. In advance of Friday's summit in Anchorage, Moscow's army pounded away at Ukraine's industrial heartland, attempting to seize the flashpoint town of Pokrovsk, a key highway and rail junction in eastern Donetsk, after repeated attempts to breach its defensive line during the week. As Putin and Trump prepared to meet, battlefield analysis site DeepState said that Pokrovsk was partially encircled. In recent days, Russian forces had reportedly seized the village of Yablunivka and the settlement of Oleksandrohrad – both in Donetsk. Ukrainian President Volodymyr Zelenskyy, who has rejected Putin's demands that Kyiv withdraw from the remaining 30 percent of Donetsk that it still controls, played down the Russian advances, saying on X that his forces were "countering" and "increasing the pressure" on the "occupier".