A new PLOS ONE study from Lehigh University introduces a computational model that predicts how electrical stimulation affects atrial fibrillation. The framework could help optimize therapy strategies and move clinicians closer to personalized cardiac care.

Scientists at TU Delft, The Netherlands, have developed a new algorithm that allows multiple autonomous drones to work together to control and transport heavy payloads, even in windy conditions. Ideal for reaching and maintaining hard-to-reach infrastructure, like offshore wind turbines. With often harsh weather, limited payload capacity and unpredictable contact with the environment, it is difficult for current drones to operate safely and effectively. The results have been published in Science Robotics.

This study presents a specialized Electronic Probe Computer (EPC60) designed to efficiently address NP-complete problems—computational challenges that become increasingly complex as their size grows. The EPC60 system, constructed with 60 fully customized FPGA-based probe computing cards, utilizes a hybrid serial-parallel computational model along with seven fully parallel probe operators. In tests conducted on large-scale 3-coloring problems, the EPC60 achieved 100% accuracy on 2000-vertex graphs in under one hour, significantly surpassing the state-of-the-art solver Gurobi, which attained only 6% accuracy. Given the theoretical mutual reducibility of NP-complete problems in polynomial time, the EPC60 emerges as a universal solver for this class of problems. Additionally, the system's modular design facilitates scalable expansion, presenting a promising hardware solution for addressing real-world optimization challenges in logistics, telecommunications, and manufacturing.