Comprised of GRD and SLC images from Sentinel-1; AIS used to create labels.

Identifying vessels that do not show up in conventional monitoring systems--known as "dark vessels"--is key to managing and securing the health

One key failure case was answers in the form of "the answer must be something that is ." Q: What might someone get from learning about science? Answer Choices: (a) headache (b) see things differently (c) increased knowledge (d) accidents (e) appreciation of nature A: The answer must be something that someone would get from learning about science. Learning about science would increase knowledge. Therefore, the answer is increased knowledge (c). These rationales, while perhaps useful to the model, read to us as opaque and unexplanatory. Sometimes the model will imply the answer that it has chosen in its question. Q: The christian rock band was on a large stage, the singer's foot got caught on a wire and he had a small what? Answer Choices: (a) commit sin (b) fail (c) disobey (d) stumble (e) boo boo A: The answer must be something that would cause the singer to stumble. The singer's foot got caught on a wire, so he would stumble.

With the increase in maritime traffic and the mandatory implementation of the Automatic Identification System (AIS), the importance and diversity of maritime traffic analysis tasks based on AIS data, such as vessel trajectory prediction, anomaly detection, and collision risk assessment, is rapidly growing. However, existing approaches tend to address these tasks individually, making it difficult to holistically consider complex maritime situations. To address this limitation, we propose a novel framework, AIS-LLM, which integrates time-series AIS data with a large language model (LLM). AIS-LLM consists of a Time-Series Encoder for processing AIS sequences, an LLM-based Prompt Encoder, a Cross-Modality Alignment Module for semantic alignment between time-series data and textual prompts, and an LLM-based Multi-Task Decoder. This architecture enables the simultaneous execution of three key tasks: trajectory prediction, anomaly detection, and risk assessment of vessel collisions within a single end-to-end system. Experimental results demonstrate that AIS-LLM outperforms existing methods across individual tasks, validating its effectiveness. Furthermore, by integratively analyzing task outputs to generate situation summaries and briefings, AIS-LLM presents the potential for more intelligent and efficient maritime traffic management.

Kyiv, Ukraine – Taras, a seasoned Ukrainian serviceman recovering from a contusion, expects "no miracles" from United States President Donald Trump's August 15 summit with his Russian counterpart, Vladimir Putin. "There's going to be no miracles, no peace deal in a week, and Putin will try to make Trump believe that it is Ukraine that doesn't want peace," the fair-haired 32-year-old with a deep brown tan acquired in the trenches of eastern Ukraine, told Al Jazeera. Taras, who spent more than three years on the front line and said he had recently shot down an explosives-laden Russian drone barging at him in a field covered with explosion craters, withheld his last name in accordance with the wartime protocol. Putin wants to dupe Trump by pandering to the US president's self-image as a peacemaker to avoid further economic sanctions, while the Russian leader seeks a major military breakthrough in eastern Ukraine, Taras said. "Putin really believes that until this winter, he will seize something sizeable, or that [his troops] will break through the front line and will dictate terms to Ukraine," Taras said.

Breakthroughs, discoveries, and DIY tips sent every weekday. Much like mermaids, the kraken, or the hafgufa, rogue waves have been regarded as a maritime myth. These waves do not always leave a lot of data behind, making it feel as if they spring up from the depths out of nowhere. However, one monster wave did leave data behind for scientists. On January 1, 1995, a monstrous 80-foot wave slammed into the Draupner oil platform in the North Sea.

A Russian attack killed three people in Ukraine's southeastern Zaporizhia region on Sunday, Governor Ivan Fedorov wrote on Telegram. A Ukrainian drone attack sparked a major fire at an oil depot in Sochi in southern Russia, the governor of Russia's Krasnodar region, Veniamin Kondratiev, said on Sunday. The fire was extinguished hours later after 120 firefighters were deployed, officials said. Russia's civil aviation authority, Rosaviatsia, briefly halted flights at Sochi's airport during the fire. Ukraine's military says it used drones to target several sites inside Russia, including refineries, an airfield and an electronics plant.

Breakthroughs, discoveries, and DIY tips sent every weekday. Fine artist Laura Shape uses quite an unexpected medium in her visual artwork. It lends striking patterns to her abstract canvases, while helping restore rivers, reefs, and wetlands. Shape uses the leather of invasive species--specifically lionfish, carp, and Burmese pythons. "I use those materials to make vibrant, textured, abstract acrylic pieces," she tells Popular Science via video call.

Falling debris from destroyed Ukrainian drones disrupted railway power supply and train operations in part of the Volgograd region, the administration of the region in Russia's south said on Sunday. There were no injuries as a result of the attacks, the administration said on Telegram, quoting Governor Andrei Bocharov. Russia downed 99 drones overnight over 12 Russian regions, the Crimean Peninsula and the Black Sea, the Russian Ministry of Defence said. Meanwhile, Russia launched a barrage of drones and missiles in an overnight attack that killed three people in Ukraine's Dnipro and the nearby region on Saturday, Ukrainian officials said. Ukraine's air force said it intercepted 183 drones and 17 missiles, but hits from 10 missiles and 25 drones were recorded in nine locations.