AsianScientist reports on the challenges of predicting rapid intensification (RI) periods in tropical cyclones due to their rarity and severe risks. A new model, RITCF-contrastive, developed by researchers from Institute of Oceanology Chinese Academy of Sciences, uses contrastive learning to improve RI TC forecasting accuracy by analyzing atmospheric and oceanic conditions alongside satellite imagery. Testing with operational data showed a 92.3% prediction rate for RI periods, indicating potential for real-time forecasting to enhance early warning systems and disaster response.
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Commentary: In suicide prevention, data must be timely, transparent and trusted
SINGAPORE reported 314 provisional suicides for 2024, while the 2023 figure was revised to 434, highlighting the importance of accurate data in suicide prevention efforts and the need for careful communication of statistics to maintain trust. Effective data collection practices from countries like Japan and Norway demonstrate that timely information can significantly improve prevention strategies and outcomes.https://www.youtube.com/watch?v=vwW9SWtbRFo Want More Context? 🔎
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