Current exposure-based therapies for PTSD, phobias, and ADHD lack personalization, real-time safety monitoring, and patient agency. ... Read more

A novel analog-to-digital conversion pre-processor uses a modulo-based signal folding method to overcome the limited dynamic range of conventional ADCs. The folded signal is reconstructed using a dedicated unfolding algorithm, enabling precise signal recovery across a wide amplitude spectrum. ... Read more

Modern ADCs must reduce cost and power consumption without compromising signal quality, particularly in power-sensitive systems such as wearables, IoT, and security devices. This technology introduces the first sub-Nyquist ADC based on an integrate-and-fire time encoding machine (IF-TEM). ... Read more

Current contact-based monitoring devices cause patient discomfort, increase infection risks, and demand significant medical staff time. ... Read more

Conventional ultrasound brightness-mode images do not provide sufficient contrast for certain anatomical structures and have a poor physical interpretation. This can highly affect the medical diagnosis reliability. ... Read more

Artificial intelligence (AI) solutions are vastly available for applications such as object segmentation, image detection, visual creation, writing assistance, and many more. There is a continuous quest to improve photograph editing software and existing AI systems. ... Read more

The alarmingly sharp increase in type 1 diabetes mellitus incidence in recent years has been coupled with a marked rise in the development of closed-loop systems aimed at continuously monitoring blood glucose levels, predicting glucose behavior and delivering adjusted insulin doses. ... Read more

Optical and dimensional limitations of images can be partially overcome today using signal enhancement technologies which typically rely on supervised, deep-learning methods. ... Read more

Searchable symmetric encryption with practical big-data performance and strong security Highlights ... Read more