Russia's air defence forces and fleet in the Black Sea have shot down eight Ukrainian drones over the Crimean port of Sevastopol, according to a Moscow-installed official. Mikhail Razvozhayev, the Russian-installed governor of Sevastopol, said the drone attack took place early on Sunday over the port of Sevastopol and the city's Balaklava and Khersones districts. "No objects, either in the city or in the water area were damaged," he said on the Telegram messaging app. One drone was shot down over the sea, five were intercepted by Russia's electronic warfare forces and two water surface drones were destroyed on the outer shore, he added. There was no immediate comment from Kyiv on the attack on the Crimean Peninsula, which Russia annexed from Ukraine in 2014.

Last month, the entire world was abuzz when five über wealthy explorers perished at the bottom of the Atlantic Ocean near the grave of the once "unsinkable ship." Disturbingly, during the same week, hundreds of war-torn refugees drowned in the Mediterranean with little news of their plight. The irony of machine versus nature illustrates how tiny humans are in the universe, and that every soul rich or poor is precious. It is with this attitude that many roboticists have been tackling some of the hardest problems in the galaxy from space exploration to desert mining to oceanography to search & rescue. Following the news of the implosion of the Titan submersible, I reached out to Professor F. Javier Diez of Rutgers University for his comment on the rescue mission and the role of robots.

Understanding how the statistical and geometric properties of neural activity relate to performance is a key problem in theoretical neuroscience and deep learning. Here, we calculate how correlations between object representations affect the capacity, a measure of linear separability. We show that for spherical object manifolds, introducing correlations between centroids effectively pushes the spheres closer together, while introducing correlations between the axes effectively shrinks their radii, revealing a duality between correlations and geometry with respect to the problem of classification. We then apply our results to accurately estimate the capacity of deep network data.

Heading towards navigational autonomy in unmanned surface vehicles (USVs) in the maritime sector can fundamentally lead towards safer waters as well as reduced operating costs, while also providing a range of exciting new capabilities for oceanic research, exploration and monitoring. However, achieving such a goal is challenging. USV control systems must, safely and reliably, be able to adhere to the international regulations for preventing collisions at sea (COLREGs) in encounters with other vessels as they navigate to a given waypoint while being affected by realistic weather conditions, either during the day or at night. To deal with the multitude of possible scenarios, it is critical to have a virtual environment that is able to replicate the realistic operating conditions USVs will encounter, before they can be implemented in the real world. Such "digital twins" form the foundations upon which Deep Reinforcement Learning (DRL) and Computer Vision (CV) algorithms can be used to develop and guide USV control systems. In this paper we describe the novel development of a COLREG-compliant DRL-based collision avoidant navigational system with CV-based awareness in a realistic ocean simulation environment. The performance of the trained autonomous Agents resulting from this approach is evaluated in several successful navigations to set waypoints in both open sea and coastal encounters with other vessels. A binary executable version of the simulator with trained agents is available at https://github.com/aavek/Aeolus-Ocean

NATO leaders are holding their annual summit as Ukraine looks to the security alliance for support in its attempt to push back invading Russian forces. The Vilnius communique, however, while emphasising NATO's support for Ukraine, gave no clear timetable on when the country might be able to join the alliance, in a major disappointment for Ukrainian President Volodymyr Zelenskyy, who had travelled to the Lithuanian capital. "Ukraine's future is in NATO," the leaders said in the joint statement on Tuesday. "We will be in a position to extend an invitation to Ukraine to join the alliance when allies agree and conditions are met," the declaration said, without specifying the conditions. The communique also touched on the Asia Pacific, with the leaders of Australia, Japan, New Zealand and South Korea all attending as NATO allies. It said China was a challenge to NATO's interests, security and values with its "ambitions and coercive policies" triggering a furious response from Beijing. And it accused Beijing and Moscow of "mutually reinforcing attempts to undercut the rules-based international order". China has said it wants peace in Ukraine, but has not condemned Russia's full scale invasion since it began in February 2022. NATO is a defensive Alliance. It is the unique, essential and indispensable transatlantic forum to consult, coordinate and act on all matters related to our individual and collective security. We reaffirm our iron-clad commitment to defend each other and every inch of Allied territory at all times, protect our one billion citizens, and safeguard our freedom and democracy, in accordance with Article 5 of the Washington Treaty. We will continue to ensure our collective defence from all threats, no matter where they stem from, based on a 360-degree approach, to fulfil NATO's three core tasks of deterrence and defence, crisis prevention and management, and cooperative security. We adhere to international law and to the purposes and principles of the Charter of the United Nations and are committed to upholding the rules-based international order. This Summit marks a milestone in strengthening our Alliance. We look forward to our valuable exchanges with the Heads of State and Government of Australia, Japan, New Zealand, and the Republic of Korea, as well as the President of the European Council and the President of the European Commission at this Summit. We also welcome the engagements with the Foreign Ministers of Georgia and the Republic of Moldova, and with the Deputy Foreign Minister of Bosnia and Herzegovina, as we continue to consult closely on the implementation of NATO's tailored support measures. This is an historic step for Finland and for NATO. For many years, we worked closely as partners; we now stand together as Allies. NATO membership makes Finland safer, and NATO stronger. Every nation has the right to choose its own security arrangements.

This paper presents a decentralized algorithm for solving distributed convex optimization problems in dynamic networks with time-varying objectives. The unique feature of the algorithm lies in its ability to accommodate a wide range of communication systems, including previously unsupported ones, by abstractly modeling the information exchange in the network. Specifically, it supports a novel communication protocol based on the "over-the-air" function computation (OTA-C) technology, that is designed for an efficient and truly decentralized implementation of the consensus step of the algorithm. Unlike existing OTA-C protocols, the proposed protocol does not require the knowledge of network graph structure or channel state information, making it particularly suitable for decentralized implementation over ultra-dense wireless networks with time-varying topologies and fading channels. Furthermore, the proposed algorithm synergizes with the "superiorization" methodology, allowing the development of new distributed algorithms with enhanced performance for the intended applications. The theoretical analysis establishes sufficient conditions for almost sure convergence of the algorithm to a common time-invariant solution for all agents, assuming such a solution exists. Our algorithm is applied to a real-world distributed random field estimation problem, showcasing its efficacy in terms of convergence speed, scalability, and spectral efficiency. Furthermore, we present a superiorized version of our algorithm that achieves faster convergence with significantly reduced energy consumption compared to the unsuperiorized algorithm.

This paper addresses the challenges of optimally placing a finite number of sensors to detect Poisson-distributed targets in a bounded domain. We seek to rigorously account for uncertainty in the target arrival model throughout the problem. Sensor locations are selected to maximize the probability that no targets are missed. While this objective function is well-suited to applications where failure to detect targets is highly undesirable, it does not lead to a computationally efficient optimization problem. We propose an approximation of the objective function that is non-negative, submodular, and monotone and for which greedy selection of sensor locations works well. We also characterize the gap between the desired objective function and our approximation. For numerical illustrations, we consider the case of the detection of ship traffic using sensors mounted on the seafloor.

The United States military says it has killed a leader of the ISIL (ISIS) group in eastern Syria in a drone strike. The strike on Friday resulted in the death of Osama al-Muhajer, the US Central Command said in a statement on Sunday. "We have made it clear that we remain committed to the defeat of ISIS throughout the region," US Central Command (CENTCOM) chief General Michael Kurilla said, using another acronym for the ISIL armed group. "ISIS remains a threat, not only to the region but well beyond," he added. According to CENTCOM, no civilians were killed in the operation but coalition forces are "assessing reports of a civilian injury".

On the Antarctic research ship Sir David Attenborough, engineers are gathered around a 4-metre square opening in the hull, known as the moon pool. A white robot floats in the water, its headlights illuminating the sides of the pool. "Now push it forward and drop it to the bottom," says Jamie Neilson, an engineering supervisor at Seatronics, the maker of this remotely operated vehicle (ROV).

Russian fighter jets have again flown dangerously close to several US MQ-9 Reaper drones operating over Syria – the second such incident of harassment in 24 hours – setting off flares and forcing Washington's unmanned aerial vehicles to take evasive manoeuvres, the United States air force said. The protest from the US air forces came as the French military said that two of its fighter jets on patrol over the Iraq-Syria border area were forced to manoeuvre "to control the risk of accident" involving a Russian Sukhoi SU-35 warplane on Thursday. The Russian aircraft had engaged in "non-professional interaction" with two of France's Rafale planes deployed to the region as part of "Operation Chammal", which seeks to contain the ISIL (ISIS) group in Iraq and Syria, the French military said. Two separate incidents on Wednesday and Thursday involving Russian warplanes and US Reaper drones were captured on video, the US said. "The events represent a new level of unprofessional and unsafe action by Russian air forces operating in Syria," the US military said.