'People say I come across as incredibly boring!' How to find love on the dating apps - whatever the obstacles Sick of swiping and messaging but never meeting anyone you like and who likes you back? Here's what worked for some lucky couples U sing dating apps to find love is commonplace these days - and yet, for many singles, it has become a double-edged sword. The perks of having a never-ending supply of potential matches at your fingertips are obvious - but the appeal of connecting and meeting with strangers is time-limited. It can be especially frustrating to feel as if you're stuck at the swiping stage. In 2023, US jeweller Shane Company found that the average American will spend about eight months using dating apps - swiping on around 3,960 profiles - before finding a partner.

'Raring to go:' the German remote-driving firm that hopes to make private car ownership redundant H aving been summoned by a few clicks in an app, the electric car slows to a halt outside the former cargo hall of Berlin's now defunct Tegel airport. No one is at the wheel, but upon a passenger stepping inside, a voice announces: "This is Bartek, I am your driver today. Please buckle up and we can be on our way." The car emits a friendly jingle, then makes its way to the former runway, where it performs a fault-free manoeuvre around a route marked by traffic cones. This is not your standard driverless car.

Denmark's Aalborg airport in the country's north has been closed after unauthorised drones were seen in its airspace, according to local authorities. Three other smaller airports in the country's southern region - Esbjerg, Sønderborg and Skrydstrup - also reported drone activity, but were not closed. The incident comes after the country's Copenhagen airport was forced to close earlier this week due to a drone incursion, which the prime minister described as the most severe attack on Danish infrastructure so far. Police said the devices could be seen from the ground, adding they couldn't rule out the activity being a prank. They were investigating who was controlling them and their motive.

The accuracy, resilience, and affordability of localisation are fundamental to autonomous robotic inspection within aircraft maintenance and overhaul (MRO) hangars. Hangars typically feature tall ceilings and are often made of materials such as metal. Due to its nature, it is considered a GPS-denied environment, with extensive multipath effects and stringent operational constraints that collectively create a uniquely challenging environment. This persistent gap highlights the need for domain-specific comparative studies, including rigorous cost, accuracy, and integration assessments, to inform a reliable and scalable deployment of a localisation system in the Smart Hangar. This paper presents the first techno-economic roadmap that benchmarks motion capture (MoCap), ultra-wideband (UWB), and a ceiling-mounted camera network across three operational scenarios: robot localisation, asset tracking, and surface defect detection within a 40 50 m hangar bay. A dual-layer optimisation for camera selection and positioning framework is introduced, which couples market-based camera-lens selection with an optimisation solver, producing camera layouts that minimise hardware while meeting accuracy targets. The roadmap equips MRO planners with an actionable method to balance accuracy, coverage, and budget, demonstrating that an optimised vision architecture has the potential to unlock robust and cost-effective sensing for next-generation Smart Hangars.

Imitation Learning (IL) algorithms offer an efficient way to train an agent by mimicking an expert's behavior without requiring a reward function. IL algorithms often necessitate access to state and action information from expert demonstrations. Although expert actions can provide detailed guidance, requiring such action information may prove impractical for real-world applications where expert actions are difficult to obtain. To address this limitation, the concept of learning from observation (LfO) or state-only imitation learning (SOIL) has recently gained attention, wherein the imitator only has access to expert state visitation information. In this paper, we present a framework for LfO and use it to survey and classify existing LfO methods in terms of their trajectory construction, assumptions and algorithm's design choices. This survey also draws connections between several related fields like offline RL, model-based RL and hierarchical RL. Finally, we use our framework to identify open problems and suggest future research directions.

To tap into the growing market of cloud gaming, whereby game graphics is rendered in the cloud and streamed back to the user as a video feed, network operators are creating monetizable assurance services that dynamically provision network resources. However, without accurately measuring cloud gaming user experience, they cannot assess the effectiveness of their provisioning methods. Basic measures such as bandwidth and frame rate by themselves do not suffice, and can only be interpreted in the context of the game played and the player activity within the game. This paper equips the network operator with a method to obtain a real-time measure of cloud gaming experience by analyzing network traffic, including contextual factors such as the game title and player activity stage. Our method is able to classify the game title within the first five seconds of game launch, and continuously assess the player activity stage as being active, passive, or idle. We deploy it in an ISP hosting NVIDIA cloud gaming servers for the region. We provide insights from hundreds of thousands of cloud game streaming sessions over a three-month period into the dependence of bandwidth consumption and experience level on the gameplay contexts.

Electric vehicle (EV) charging loads identification from behind smart meter recordings is an indispensable aspect that enables effective decision-making for energy distributors to reach an informed and intelligent decision about the power grid's reliability. When EV charging happens behind the meter (BTM), the charging occurs on the customer side of the meter, which measures the overall electricity consumption. In other words, the charging of the EV is considered part of the customer's load and not separately measured by the Distribution Network Operators (DNOs). DNOs require complete knowledge about the EV presence in their network. Identifying the EV charging demand is essential to better plan and manage the distribution grid. Unlike supervised methods, this paper addresses the problem of EV charging load identification in a non-nonintrusive manner from low-frequency smart meter using an unsupervised learning approach based on anomaly detection technique. Our approach does not require prior knowledge of EV charging profiles. It only requires real power consumption data of non-EV users, which are abundant in practice. We propose a deep temporal convolution encoding decoding (TAE) network. The TAE is applied to power consumption from smart BTM from Victorian households in Australia, and the TAE shows superior performance in identifying households with EVs.

While not all injuries can be prevented, these new materials offer a new tool for surfers and divers. Breakthroughs, discoveries, and DIY tips sent every weekday. While you're more likely to be killed by a lightning strike or boat accident than a shark bite, their razor sharp teeth and immense bite force are still dangerous. Surfers-who the predators can often mistake for seals -and communities that rely on ocean tourism dollars are particularly at high risk from shark bites. Now, Australian shark experts have tested four new bite-resistant materials to see how well they reduce injuries and blood loss.

Vladimir Putin will keep driving the war forward wider and deeper if he is not stopped, Ukraine's President Zelensky has warned. Speaking at the UN's General Assembly in New York, Zelensky said more countries would be met with Russian aggression unless allies displayed a united front and ramped up support. He said all nations were threatened by a global arms race, as military technology advances, adding that weapons decide who survives and called for global rules on AI. His comments come after US President Donald Trump shifted his position on the Russia-Ukraine war, saying for the first time that Ukraine could win back all of its land. Zelensky criticised international institutions, suggesting they are too weak to offer Ukraine safety guarantees, adding - in apparent reference to Nato - that being part of a long-standing military alliance doesn't automatically mean you are safe. We are now living through the most destructive arms race in human history, he said.

The commander of Nasa's next mission to the Moon said that he and his crew would see things that no human has ever seen. Reid Wiseman told a news conference that it was likely that his spacecraft would fly over large areas of the Moon that previous Apollo missions had never mapped. Yesterday, Nasa announced it hoped it would be able to launch the first crewed Moon mission in 50 years as early as February 2026 . Mission specialist Christina Koch explained that the astronauts would be able to study the lunar surface in exquisite detail for a full three hours. Believe it or not, human eyes are one of the best scientific instruments that we have, she said.