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Ashok, Ning, and colleagues report a new class of origami-inspired electromagnetic waveguides that can fold, deploy, and reconfigure. These shape-morphable designs enable efficient microwave transmission in compact, confined systems.
Conventional wet purification systems face scalability and durability challenges. Junkai Ren and colleagues report a porous ceramic-based bubble-enhanced filtration system achieving scalable, durable, and renewable wet particle removal while enabling multifunctional air purification.
Alex Vicente Sola and authors introduce a new high-speed LiDAR-based imaging modality driven by the time-of-arrival of individually detected photons and reconstructed by a spiking convolutional neural network, allowing the system to run fully asynchronously.
Johannes Grünwald and colleagues report that active electroencephalographic (EEG) electrodes provide recordings as reliable as traditional passive ones during transcranial magnetic stimulation (TMS). This supports broader adoption of active EEG electrodes for TMS by reducing preparation time and technical limitations.
Rory D. Bennett and colleagues have shown that real-time prostate tracking is possible using object detection and surface-based ultrasound scans. This opens the door to development of a prostate cancer screening workflow that is not reliant on highly skilled clinicians.
Tracking unknown targets under forest cover is challenging. Rakesh John Amala Arokia Nathan and colleagues present a fully autonomous drone swarm, field-validated and designed to handle sensor noise, that adaptively samples a synthetic aperture to detect and track anomalous targets.
Qihui Wu and colleagues propose a brain-inspired embodied learning method for anomaly active target tracking, enabling dynamic switching between normal and anomaly handling modes. This improves tracking robustness in complex real-world environments
Low-grade heat is often wasted because conventional technologies cannot use it effectively. Moreno Resendiz and colleagues report a thermomagnetic generator that powers IoT sensors using small temperature differences between ocean and ambient air.
Selecting the best cell lines for antibody production is a lengthy process in biomanufacturing. Penghua Wang and colleagues introduced a hybrid model that uses early-stage data to accurately predict final yields, accelerating the clone selection timeline.
Meiling Guan and colleagues report a receiver-side method that reshapes distorted light into optical pin beam, stabilizing free-space laser communication. It achieves 100 Gbps stable communication over 1 km.
Chang Li and colleagues propose an edge pipelined intelligent computing approach for voltage regulation in PV-rich distribution networks, improving efficiency, alleviating voltage violations, and maintaining robust performance under partial observation.
Low-power beamforming technologies are required for wireless links at high radio frequencies. Mitchell Nichols and colleagues report an optical microring beamformer with low area and power consumption, enabling compact and large-scale antenna arrays.
Identifying layup configurations that achieve maximum auxetic characteristics and thereby maximize performance enhancements is challenging. Yuze Li and colleagues introduce an intelligent machine learning–aided inverse design method to efficiently identify layups with optimal auxetic performance.
Drone flight safety is challenged in the landing phase, especially in windy conditions. Hao Xiong and colleagues propose a reinforcement learning-based trajectory planner to balance multiple landing-related objectives based on onboard wind sensory capability.
Hadrien Fasseaux and colleagues propose a Fourier-based method to analyze fiber sensor signals with coarse interrogators. This advance enables affordable, portable biosensing for healthcare and beyond.
Perovskite solar modules are typically limited by inactive areas caused by scribing steps. Andrés Soto and colleagues report a method using a single UV nanosecond laser to reduce these dead areas, achieving high geometric fill factors.
The excitation-inhibition (E/I) balance in neural circuits is crucial for homeostasis. Hiroshi Yokoyama and colleagues developed a data assimilation method to detect E/I balance changes using only EEG signals, validating it by demonstrating correlation with TMS-EEG-based methods.
Ruhit Sinha and Anne Staples survey current computational modelling approaches for analysing hollow fibre haemodialysers. They assess computational strategies and address open issues that will help develop the next generation of artificial kidneys.
Joel Strickland and colleagues present a conformal deep learning framework for non-invasive prediction of core body temperature in extreme environments. The method enhances accuracy and delivers calibrated uncertainty estimates for reliable, real-time safety monitoring.
Ishan Goswami and colleagues report engineering robust physiologically relevant tissues in microphysiological systems utilizing highly tuneable interfacial barriers. This has applications for drug discovery and disease modelling.
