Supporters of Global Sumud Flotilla gather to show support in Sidi Bou Said port, Tunisia, on Wednesday. SIDI BOU SAID, Tunisia - The Global Sumud Flotilla (GSF), an international aid initiative to deliver vital supplies to the Gaza Strip, said Wednesday that one of its boats was attacked by a drone at a Tunisian port in the second such strike in two days. The GSF, which is seeking to break Israel's naval blockade and deliver humanitarian aid to war-torn Gaza using civilian boats, said in a statement that all passengers and crew were unharmed. The GSF reported the first attack on Tuesday, saying one of its vessels had been struck by a drone in Tunisian waters at the Sidi Bou Said port. Tunisian authorities said the reports were false. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

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? Polish and NATO forces have shot down drones violating the country's airspace during a Russian aerial attack on neighbouring Ukraine. Fighter jets were scrambled early on Wednesday as more than a dozen drones entered Polish airspace, the Polish military said.

In the critical 72 hours after an earthquake or explosion, a race against the clock begins to find survivors. When a powerful earthquake hit central Italy on 24 August 2016, killing 299 people, over 5 000 emergency workers were mobilised in search and rescue efforts that saved dozens from the rubble in the immediate aftermath. The pressure to move fast can create risks for first responders, who often face unstable environments with little information about the dangers ahead. But this type of rescue work could soon become safer and more efficient thanks to a joint effort by EU and Japanese researchers. Rescue organisations, research institutes and companies from both Europe and Japan worked together from 2019 to 2023 to develop a new generation of tools blending robotics, drone technology and chemical sensing to transform how emergency teams operate in disaster zones.

What we know about Gaza flotilla'drone attack' NewsFeed What we know about Gaza flotilla'drone attack' Activists on the Global Sumud Flotilla to Gaza say their main vessel was hit by a drone attack in Tunisia. Tunisian authorities said it was an accidental fire. Here's what we know so far. Gaza City residents react to Israel's forced expulsion orders

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? On Sunday, Russia launched its largest drone and missile attack since the war began, firing a total of 823 projectiles into Ukraine. The attack killed at least four people, wounded 44, and caused damage to a key building in Kyiv's government district, making it the first on the site since the full-fledged war began in February 2022.

How dangerous is the situation in the West Bank? What does survival look like inside Gaza City? The Gaza-bound Global Sumud Flotilla (GSF) says a drone has struck its main ship in the Tunisian port of Sidi Bou Said, causing a fire, but that all its passengers and crew were safe. A spokesman for the GSF blamed Israel for the incident, which occurred late on Monday, but the Tunisian National Guard said reports of a drone attack were "completely unfounded". The GSF, however, insisted the incident was a drone attack and said it would provide more details on Tuesday morning.

How dangerous is the situation in the West Bank? What does survival look like inside Gaza City? Video shows the moment activists from the Global Sumud Fotilla to Gaza say one of their boats was struck by a drone at Sidi Bou Said port in Tunisia. Fire damage was caused on the main deck of the vessel, which was carrying GSF steering committee members. Nepal'Gen Z' protest death toll climbs, parliament stormed Israel wants to'destroy Gaza City, not occupy it'

This paper presents an adaptive coverage control method for a fleet of off-road and Unmanned Ground Vehicles (UGVs) operating in dynamic (time-varying) agricultural environments. Traditional coverage control approaches often assume static conditions, making them unsuitable for real-world farming scenarios where obstacles, such as moving machinery and uneven terrains, create continuous challenges. To address this, we propose a real-time path planning framework that integrates Unmanned Aerial Vehicles (UAVs) for obstacle detection and terrain assessment, allowing UGVs to dynamically adjust their coverage paths. The environment is modeled as a weighted directed graph, where the edge weights are continuously updated based on the UAV observations to reflect obstacle motion and terrain variations. The proposed approach incorporates Voronoi-based partitioning, adaptive edge weight assignment, and cost-based path optimization to enhance navigation efficiency. Simulation results demonstrate the effectiveness of the proposed method in improving path planning, reducing traversal costs, and maintaining robust coverage in the presence of dynamic obstacles and muddy terrains.

In various scenarios such as multi-drone surveillance and search-and-rescue operations, deploying multiple robots is essential to accomplish multiple tasks at once. Due to the limited communication range of these vehicles, a decentralised task allocation algorithm is crucial for effective task distribution among robots. The consensus-based bundle algorithm (CBBA) has been promising for multi-robot operation, offering theoretical guarantees. However, CBBA demands continuous communication, leading to potential congestion and packet loss that can hinder performance. In this study, we introduce an event-driven communication mechanism designed to address these communication challenges while maintaining the convergence and performance bounds of CBBA. We demonstrate theoretically that the solution quality matches that of CBBA and validate the approach with Monte-Carlo simulations across varying targets, agents, and bundles. Results indicate that the proposed algorithm (ED-CBBA) can reduce message transmissions by up to 52%.

The You Only Look Once (YOLO) architecture is crucial for real-time object detection. However, deploying it in resource-constrained environments such as unmanned aerial vehicles (UAVs) requires efficient transfer learning. Although layer freezing is a common technique, the specific impact of various freezing configurations on contemporary YOLOv8 and YOLOv10 architectures remains unexplored, particularly with regard to the interplay between freezing depth, dataset characteristics, and training dynamics. This research addresses this gap by presenting a detailed analysis of layer-freezing strategies. We systematically investigate multiple freezing configurations across YOLOv8 and YOLOv10 variants using four challenging datasets that represent critical infrastructure monitoring. Our methodology integrates a gradient behavior analysis (L2 norm) and visual explanations (Grad-CAM) to provide deeper insights into training dynamics under different freezing strategies. Our results reveal that there is no universal optimal freezing strategy but, rather, one that depends on the properties of the data. For example, freezing the backbone is effective for preserving general-purpose features, while a shallower freeze is better suited to handling extreme class imbalance. These configurations reduce graphics processing unit (GPU) memory consumption by up to 28% compared to full fine-tuning and, in some cases, achieve mean average precision (mAP@50) scores that surpass those of full fine-tuning. Gradient analysis corroborates these findings, showing distinct convergence patterns for moderately frozen models. Ultimately, this work provides empirical findings and practical guidelines for selecting freezing strategies. It offers a practical, evidence-based approach to balanced transfer learning for object detection in scenarios with limited resources.