Singapore Science News API

{
    "totalArticles": 17434,
    "articles": [
        {
            "id": "d1e91d82a991f21a1caa2ecc85d49142",
            "title": "Integrating digital twin technology with deep reinforcement learning for sustainable marine fishery resource management",
            "description": "Marine fishery ecosystems face unprecedented pressure from overfishing and climate variability, and these mounting threats call for management tools that go beyond traditional static quota systems. This paper puts forward an integrated framework that couples digital twin (DT) technology with deep reinforcement learning (DRL) to tackle sustainable fishery resource management. We build a five-layer hierarchical architecture whose centerpiece is a high-fidelity digital twin that mirrors fishery dynamics through explicit state-transition and observation equations rather than abstract placeholders. A Proximal Policy Optimization (PPO) agent operates within this simulated environment, receiving multidimensional state inputs—resource stocks, oceanographic conditions, fleet operations—and optimizing a composite reward function whose weights we set to $${\\omega }_{1}=0.3$$ (economic), $${\\omega }_{2}=0.3$$ (ecological), and $${\\omega }_{3}=0.4$$ (sustainability). We conduct both comparative experiments and ablation studies using East China Sea fishery data spanning 2010–2023. The ablation study, which isolates the digital twin contribution by comparing PPO with and without DT integration, confirms that the DT alone accounts for a 31.9% reward improvement. Overall, our method achieves a resource recovery index (RRI) of 0.83, outperforming traditional maximum sustainable yield management by 97.6% and standard deep Q-networks by 36.1%. Spatial heatmaps and temporal effort-control time series generated from the learned policy reveal ecologically sensible seasonal and spatial harvest patterns. This research establishes a virtual–real fusion paradigm for intelligent fishery governance and provides decision-support tools for sustainability challenges in an era of accelerating environmental change.",
            "content": "1. This work was supported by the Research on Optimal Path Planning Algorithm for Multi-Warehouse Collaborative Drone Scheduling Based on ABM Model (Grant No. Y202559209) from the 2025 General Scientific Research Project of the Department of Educatio... [2131 chars]",
            "url": "https://www.nature.com/articles/s41598-026-55594-7?error=cookies_not_supported&code=f4769212-8d55-4ad3-9ead-677aedf64c1f",
            "image": "https://www.nature.com/static/images/favicons/nature/favicon-48x48-b52890008c.png",
            "publishedAt": "2026-06-04T19:00:17Z",
            "lang": "en",
            "source": {
                "id": "7abf0df285fbe93cdccffcc7c4088737",
                "name": "Nature",
                "url": "https://www.nature.com"
            }
        },
        {
            "id": "150266990504a6bf351d5c52ccbc5547",
            "title": "Why university-level chemistry education in the UK is under threat",
            "description": "University-level chemistry education in the UK is facing mounting pressures that threaten its long-term viability. Without decisive intervention, we risk losing the scientific talent and capacity needed to retain the UK’s position as a leader in innovation.",
            "content": "Chemistry in UK higher education data pack. RSC https://www.rsc.org/policy-and-campaigning/policy-library/chemistry-higher-education-data-and-messaging-pack (2025).\nPlackett, B. British students decline to study chemistry. Chemical & Engineering News... [1453 chars]",
            "url": "https://www.nature.com/articles/s41570-026-00839-2?error=cookies_not_supported&code=d1d131a3-d40f-4c34-9bdf-ede42caa1535",
            "image": "https://media.springernature.com/m685/springer-static/image/art%3A10.1038%2Fs41570-026-00839-2/MediaObjects/41570_2026_839_Fig1_HTML.png",
            "publishedAt": "2026-06-04T13:46:46Z",
            "lang": "en",
            "source": {
                "id": "7abf0df285fbe93cdccffcc7c4088737",
                "name": "Nature",
                "url": "https://www.nature.com"
            }
        },
        {
            "id": "48b6154ef25777307aba510dbc568009",
            "title": "This Jellyfish Has 24 Eyes - A Biologist Explains What It Actually Sees With Them",
            "description": "The box jellyfish is famous for its venom, but its bizarre collection of 24 eyes may be even more remarkable than its sting.",
            "content": "When picturing a jellyfish, what comes to mind for most people is a simple drifting blob: no brain, no bones, no plan. Just a slimy sea-creature at the mercy of currents. Eyes and vision would be one of the last features to come to mind — yet some je... [7721 chars]",
            "url": "https://www.yahoo.com/news/science/articles/jellyfish-24-eyes-biologist-explains-123000133.html",
            "image": "https://s.yimg.com/lo/mysterio/api/6bbeffb765acb7b1b874fc5a32cf6df7749dee5f74a0e524b69a7f8573a4e87c/lightyear_networkapi/resizefill_w958_h539;quality_80;format_webp/https:%2F%2Fmedia.zenfs.com%2Fen%2Fforbes_contributor_845%2F7e0b6e925030416b5ff998fb08410b32",
            "publishedAt": "2026-06-04T12:30:00Z",
            "lang": "en",
            "source": {
                "id": "99e8a2cb4638bb798cf9167e5af5b83b",
                "name": "Yahoo",
                "url": "https://www.yahoo.com"
            }
        }
    ]
}