Life cycle assessment (LCA) is the gold-standard method for quantifying the environmental footprint of products and processes—from climate change to resource depletion. 

Scientists have developed a hierarchical Transformer-based artificial intelligence model that predicts RNA splice sites across DNA sequences up to 100,000 base pairs long while preserving single-nucleotide resolution. The system captures long-range regulatory interactions that conventional approaches often miss and visualizes the sequence regions influencing its predictions. The approach achieved state-of-the-art performance on multiple benchmark datasets and may support future studies in genetic diseases, cancer, precision medicine, genomic medicine, and therapeutic development.

The Hebrew University of Jerusalem proudly congratulates two of its outstanding researchers on receiving prestigious European Research Council (ERC) Proof of Concept Grants for 2026. The grants support ERC-funded researchers in translating groundbreaking discoveries into innovative applications, technologies, and services with real-world impact.

This study presents a hybrid dynamic best model selection algorithm for real-time building fire prediction using IoT-enabled smoke, temperature, and humidity sensors. Validated on a custom laboratory dataset and live sensor streams, the system dynamically selected the best machine-learning classifier and achieved 99.57% accuracy, 99.37% precision, 99.79% recall, and low error, improving adaptability and early fire detection.

Patients with untreatable conditions such as sight loss or loss of motor-function could be closer to a viable technology for restoring their lost sense, within a faster time frame. This is due to the discovery that advanced brain interfacing technology used for both touch and vision prostheses, is in fact almost the same, despite being developed completely separately for more than 50 years. The comprehensive review in which this discovery has first been made, was published in Nature Reviews Bioengineering, and was led by Giacomo Valle, Assistant Professor at Chalmers University of Technology, in Sweden.