arrival direction
The First Radio Signal From Comet 3I/Atlas Ends the Debate About Its Nature
An observatory detected the first radio signal from the interstellar object 3I/Atlas. An image of the interstellar comet 3I/Atlas, captured by the Hubble telescope on July 21, 2025. More evidence has emerged to support the natural origin of comet 3I/Atlas . After several weeks of conspiracy theories, social media debates, and speculation on popular podcasts such as Joe Rogan's, this interstellar object is still a comet . The most recent confirmation came from an observatory in South Africa that detected the first radio signal from 3I/Atlas.
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- Health & Medicine > Therapeutic Area > Cardiology/Vascular Diseases (0.49)
Efficient Real-Time Aircraft ETA Prediction via Feature Tokenization Transformer
Huang, Liping, Zhang, Yicheng, Yin, Yifang, Zhang, Sheng, Zhang, Yi
Estimated time of arrival (ETA) for airborne aircraft in real-time is crucial for arrival management in aviation, particularly for runway sequencing. Given the rapidly changing airspace context, the ETA prediction efficiency is as important as its accuracy in a real-time arrival aircraft management system. In this study, we utilize a feature tokenization-based Transformer model to efficiently predict aircraft ETA. Feature tokenization projects raw inputs to latent spaces, while the multi-head self-attention mechanism in the Transformer captures important aspects of the projections, alleviating the need for complex feature engineering. Moreover, the Transformer's parallel computation capability allows it to handle ETA requests at a high frequency, i.e., 1HZ, which is essential for a real-time arrival management system. The model inputs include raw data, such as aircraft latitude, longitude, ground speed, theta degree for the airport, day and hour from track data, the weather context, and aircraft wake turbulence category. With a data sampling rate of 1HZ, the ETA prediction is updated every second. We apply the proposed aircraft ETA prediction approach to Singapore Changi Airport (ICAO Code: WSSS) using one-month Automatic Dependent Surveillance-Broadcast (ADS-B) data from October 1 to October 31, 2022. In the experimental evaluation, the ETA modeling covers all aircraft within a range of 10NM to 300NM from WSSS. The results show that our proposed method method outperforms the commonly used boosting tree based model, improving accuracy by 7\% compared to XGBoost, while requiring only 39\% of its computing time. Experimental results also indicate that, with 40 aircraft in the airspace at a given timestamp, the ETA inference time is only 51.7 microseconds, making it promising for real-time arrival management systems.
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- North America > United States > Florida > Hillsborough County > Tampa (0.04)
- Europe > France > Provence-Alpes-Côte d'Azur (0.04)
- Transportation > Air (1.00)
- Transportation > Infrastructure & Services > Airport (0.55)
Analysis of Fluorescence Telescope Data Using Machine Learning Methods
Zotov, Mikhail, Zakharov, Pavel
Fluorescence telescopes (FTs) are an important part of all major modern experiments aimed at studying ultra-high energy cosmic rays (UHECRs, E 1 EeV), both the Pierre Auger Observatory [1] and the Telescope Array [2]. FTs register scintillation light emitted from nitrogen molecules in the air excited during the development of extensive air showers (EASs) generated by UHECRs. Measurements are performed in clear moonless nights in the near-UV band. The future cosmic ray observatories are also planned to employ the fluorescence technique, both in ground-based experiments like GCOS [3] and in orbital experiments like K-EUSO [4] or POEMMA [5].
- Europe > Russia > Central Federal District > Moscow Oblast > Moscow (0.05)
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