How successful is Ukraine's'gas war' against Russia? How will Putin travel to Hungary with an ICC arrest warrant? How much of Europe's oil still comes from Russia? How Russia's new tactics pose new winter threat to Ukraine The Russian drone strike was surgically precise and destroyed a giant transformer at a key power station in the Ukrainian capital. "There's nothing left to repair," Mykola Svyrydenko, who lives close to Thermal Station 5, a sprawling, Soviet-era structure with two giant steam pipes that provides electricity and heat to hundreds of thousands of Kyiv's residents, told Al Jazeera.

A novel autonomous chunk-based aerial additive manufacturing framework is presented, supported with experimental demonstration advancing aerial 3D printing. An optimization-based decomposition algorithm transforms structures into sub-components, or chunks, treated as individual tasks coordinated via a dependency graph, ensuring sequential assignment to UA Vs considering inter-dependencies and printability constraints for seamless execution. A specially designed hexacopter equipped with a pressurized canister for lightweight expandable foam extrusion is utilized to deposit the material in a controlled manner. To further enhance precise execution of the printing, an offset-free Model Predictive Control mechanism is considered compensating reactively for disturbances and ground effect during execution. Additionally, an interlocking mechanism is introduced in the chunking process to enhance structural cohesion and improve layer adhesion. Extensive experiments demonstrate the framework's effectiveness in constructing precise structures of various shapes, while seamlessly adapting to practical challenges, proving its potential for a transformative leap in aerial robotic capability for autonomous construction. A video with the overall demonstration can be found here: https://youtu.be/WC1rLMLKEg4. Preprint submitted to Journal of Automation In Construction February 27, 2025 1. Introduction In recent times, ground breaking advancement in additive manufacturing, seamlessly integrated with autonomous robotics, are unlocking an exciting frontier in next generation construction and manufacturing process. Additive manufacturing has demonstrated a paradigm shift impact, addressing complex manufacturing processes with unprecedented precision and efficiency. Its transformative potential is becoming increasingly evident as it evolves and finds applications across a wide range of industries [1, 2, 3], while simultaneously paving the way for further innovations in the future. An intriguing development is its recent integration into the construction industry, capitalizing on its ability to automate construction processes, provide extensive design flexibility, and construct intricate structures designed using Computer-Aided Design (CAD) software [4, 5]. Numerous studies have demonstrated the design and deployment of large-scale robotic arms and gantry systems for printing building components and even entire houses using a variety of base materials [6]. A key advantage of such methods is their ability to adapt with high level of automation throughout the construction process, making them particularly well-suited for deployment in remote, inaccessible, and harsh environments[7, 8]. Notable examples include disaster-stricken areas, such as regions impacted by fires and earthquakes, where the rapid construction of shelters and basic infrastructure is imperative.

During the pandemic, Tokyo's bustling Meiji University campus stood still. My students were confined to their homes, appearing only as small figures on my screen during Zoom lectures on human-computer interaction. I spent the days in my lab, looking for ways to pass the time. On a particularly bland day in 2020, I was reminiscing about how, before the pandemic, Tokyo used to be packed with people who had flown across the world to enjoy the exciting food scene. But now restaurants were empty and people longed for foods they once relished.

A sample of material collected from the surface of the near-Earth asteroid Bennu has been found to contain abundant water and carbon, the US space agency NASA said, offering more evidence for a theory that life on Earth was seeded from outer space. The findings were announced on Wednesday as NASA gave the public a first glimpse of what scientists found inside a sealed capsule that was returned to Earth last month after carrying material scooped from the 4.5-billion-year-old asteroid's surface by the OSIRIS-REx spacecraft. "This is the biggest carbon-rich asteroid sample ever returned to Earth," NASA administrator Bill Nelson said at a press event at the Johnson Space Center in Houston, where the first images of black dust and pebbles were revealed. Carbon accounted for almost 5 percent of the sample's total weight, and was present in both organic and mineral form, while the water was locked inside the crystal structure of clay minerals, Nelson said. The findings were made through a preliminary analysis involving scanning the sample with electron microscopy, X-ray computed tomography and more.

Scientists at the United States space agency NASA found "black dust and debris" when they opened the space capsule that recently returned to Earth with the largest asteroid sample ever brought back from space. NASA said on Tuesday that researchers discovered "dust and debris on the avionics deck of the Osiris-REx science canister when the initial lid was removed today". The space agency did not specify whether the materials discovered on opening the lid of the probe definitely belonged to the asteroid, though NASA said on social media that "scientists gasped as the lid was lifted from the [Osiris-REx] asteroid sample return canister". "A scientific treasure box," NASA Astromaterials said in a social media post. "Dark powder and sand-sized particles" were found on "the inside of the lid and base", NASA said.

We present the design and operation of tadpole-mimetic robots prepared for a study of the parenting behaviors of poison frogs, which pair bond and raise their offspring. The mission of these robots is to convince poison frog parents that they are tadpoles, which need to be fed. Tadpoles indicate this need, at least in part, by wriggling with a characteristic frequency and amplitude. While the study is in progress, preliminary indications are that the TadBots have passed their test, at least for father frogs. We discuss the design and operational requirements for producing convincing TadBots and provide some details of the study design and plans for future work.

Join me as I share my brutally honest first impressions of Atomic Heart in this review of the game's first 2 hours. From bugs and glitches to moments of pure rage, I delve into the highs and lows of my gameplay experience, providing an unfiltered assessment of this highly anticipated title. Check out my store – https://jakeydesigns.com Game Description: Atomic Heart is a first-person shooter video game with role-playing elements. The combat consists of shooting and slashing with improvised weapons. A wide variety of enemies are featured, which may be mechanical, biomechanical, biological, and some of which are airborne.

Transparent objects are common in day-to-day life and hence find many applications that require robot grasping. Many solutions toward object grasping exist for non-transparent objects. However, due to the unique visual properties of transparent objects, standard 3D sensors produce noisy or distorted measurements. Modern approaches tackle this problem by either refining the noisy depth measurements or using some intermediate representation of the depth. Towards this, we study deep learning 6D pose estimation from RGB images only for transparent object grasping. To train and test the suitability of RGB-based object pose estimation, we construct a dataset of RGB-only images with 6D pose annotations. The experiments demonstrate the effectiveness of RGB image space for grasping transparent objects.

Nondestructive evaluation methods play an important role in ensuring component integrity and safety in many industries. Operator fatigue can play a critical role in the reliability of such methods. This is important for inspecting high value assets or assets with a high consequence of failure, such as aerospace and nuclear components. Recent advances in convolution neural networks can support and automate these inspection efforts. This paper proposes using residual neural networks (ResNets) for real-time detection of pitting and stress corrosion cracking, with a focus on dry storage canisters housing used nuclear fuel. The proposed approach crops nuclear canister images into smaller tiles, trains a ResNet on these tiles, and classifies images as corroded or intact using the per-image count of tiles predicted as corroded by the ResNet. The results demonstrate that such a deep learning approach allows to detect the locus of corrosion cracks via smaller tiles, and at the same time to infer with high accuracy whether an image comes from a corroded canister. Thereby, the proposed approach holds promise to automate and speed up nuclear fuel canister inspections, to minimize inspection costs, and to partially replace human-conducted onsite inspections, thus reducing radiation doses to personnel.

A 65-year-old woman in Utah's Snow Canyon State Park got some unexpected help from a drone operated by the local sheriff's department, after injuring her ankle while hiking with friends. While walking near the edge of Island in the Sky, a famous canyoneering and rock climbing route, she slipped and fell several feet, injuring her ankle to the point where she could no longer stand or support her own weight. The group of three friends she was with called the sheriff's search and rescue team rather than attempt to carry her back down the steep and sandy trail themselves. Search and rescue workers from the Washington Country Sheriff's Department in Utah used a drone to deliver then 660 feet of twine to help setup a rappelling system to get an injured hiker down from a clifftop The sheriff's team decided to bring the woman down from the 400-foot-tall cliff, the equivalent of 40 stories, by strapping her to a stretcher and using a rappelling system to guide her down. The only problem was they didn't have enough rope to reach actually reach the ground.