SUN-DT moves towards the full digitalization of tower CSP plants to improve efficiency and reduce operational costs
Business Announcement
Updates every hour. Last Updated: 2-Jan-2026 13:11 ET (2-Jan-2026 18:11 GMT/UTC)
The European project SUN-DT, in which IMDEA Networks participates and which is funded by Horizon Europe, officially launched its activities in October 2025. Formed by a consortium of nine international organizations and coordinated by CENER, the initiative aims to drive the digital transition of tower concentrated solar power (CSP) plants.
A new evidence brief, based on a study by the Juno Evidence Alliance conducted in collaboration with CABI’s One Health Hub, has highlighted that a One Health approach is needed in research into zoonotic disease risks around the world.
Researchers at Imperial College London, developed a new method to combine infrastructure-based traffic data with vehicle-based data. They demonstrate that adding traffic covariates increases accuracy and the use of the No-U-Turn Sampler (NUTS) reduces the computational running time.
Image reconstruction—the process of recovering clear images from incomplete or noisy data—has been advancing rapidly through deep learning. Yet most existing approaches rely on costly supervised training and lack theoretical transparency. A new survey maps the rise of unsupervised deep learning for image reconstruction, from traditional denoising-based priors to modern diffusion models. These methods learn structured visual information directly from unlabeled data, and have achieved impressive performance across various fields, including biomedical imaging and remote sensing. The study shows how unsupervised learning based image reconstruction unites neural network efficiency with solid mathematical foundations to achieve both interpretability and flexibility, offering a blueprint for next-generation imaging systems.