Laying the groundwork to diagnose speech impairments in children with clinical AI #ASA188
Reports and Proceedings
This month, we’re focusing on artificial intelligence (AI), a topic that continues to capture attention everywhere. Here, you’ll find the latest research news, insights, and discoveries shaping how AI is being developed and used across the world.
Updates every hour. Last Updated: 6-Nov-2025 00:11 ET (6-Nov-2025 05:11 GMT/UTC)
Speech and language impairments affect over a million children every year, and identifying and treating these conditions early is key to helping these children overcome them. Marisha Speights has built a data pipeline to train clinical artificial intelligence tools for childhood speech screening and will present her work Monday, May 19, at the 188th ASA Meeting. They collected a representative sample of speech from children across the country, verified transcripts and enhanced audio quality using their custom software, and provided a platform that will enable detailed annotation by experts.
A research article published by the Peking University presented a control framework for exoskeletons based on environmental perception, which effectively integrates environmental information and human kinematic data, improves the accuracy and lead time of transition detection, thereby enhancing smooth switching of control strategies across different terrains. Additionally, the adoption of a learning-free method eliminates the need for data collection and model training, demonstrating strong generalization capabilities across users.
Strategically arranging histidine residues inside a protein cage is a promising approach to create artificial enzymes, reports researchers from Institute of Science Tokyo. The engineered protein cage mimics natural enzymes using simple amino acids without any metal cofactors, overcoming a major limitation in artificial enzyme design. Molecular simulations confirmed that the confined environment within the protein cage enhances catalytic efficiency, offering a new route to develop sustainable biocatalysts.
Two Case Western Reserve University engineering faculty have been awarded U.S. National Science Foundation (NSF) Faculty Early Career Development Program (CAREER) grants. Computer scientist An Wang and environmental engineer Bridget Hegarty were each awarded a five-year grant to support their research programs. Hegarty also received a $1 million grant from the Department of Housing and Urban Development.
This article examines the potential of Artificial Intelligence-driven Distributed Acoustic Sensing (AI+DAS) technology in engineering applications. Based on fiber optic monitoring, DAS enables real-time acoustic signal monitoring by detecting disturbances along the fiber, offering long measurement distances, high spatial resolution, and a large dynamic range. The article outlines the basic principles and demodulation methods of DAS using Φ-OTDR technology, highlighting AI's role in data processing and event recognition. By integrating AI algorithms, DAS systems enhance monitoring accuracy and reliability. Additionally, the article reviews AI+DAS applications across various fields, including engineering and geology, and discusses challenges such as model complexity and resource demands. Overall, it aims to foster interdisciplinary collaboration and support digital transformation in industrial scenarios.
Deep-penetration light-triggered pyroptosis based on nanomedicine for tumor precision therapy still remains challenging. Towards this goal, Scientist in China reported a supramolecular engineering strategy to construct Pt(IV)-coordinated supra-(carbon dots) with NIR-activated photocatalytic capacity to trigger tumor pyroptosis, thereby evoking anti-tumor immune responses to suppress distant tumor and prevent cancer metastasis. The finding will open new avenues for precision phototherapy in future clinical oncology by supramolecular-mediated nanomedicine with deep-penetration light triggered pyroptosis.