Predicting RNA Structure and Dynamics with Deep Learning and Solution Scattering.

Advanced deep learning and statistical methods can predict structural models for RNA molecules. However, RNAs are flexible, and it remains difficult to describe their macromolecular conformations in solutions where varying conditions can induce conformational changes. Small-angle X-ray scattering (SAXS) in solution is an efficient technique to validate structural predictions by comparing the experimental SAXS profile with those calculated from predicted structures.

Predicting RNA structure and dynamics with deep learning and solution scattering.

Advanced deep learning and statistical methods can predict structural models for RNA molecules. However, RNAs are flexible, and it remains difficult to describe their macromolecular conformations in solutions where varying conditions can induce conformational changes. Small-angle x-ray scattering (SAXS) in solution is an efficient technique to validate structural predictions by comparing the experimental SAXS profile with those calculated from predicted structures.

Exploring Transportation Challenges and Opportunities for Mobility-Vulnerable Populations Through the Social-Ecological Model.

Community mobility is a vital activity of daily living. Mobility-vulnerable populations-individuals with incomes below the federal poverty threshold, minorities, individuals with disabilities, and older adults-face transit disparities. Advanced technologies (e.

Integrating federated learning for improved counterfactual explanations in clinical decision support systems for sepsis therapy.

In recent years, we have witnessed both artificial intelligence obtaining remarkable results in clinical decision support systems (CDSSs) and explainable artificial intelligence (XAI) improving the interpretability of these models. In turn, this fosters the adoption by medical personnel and improves trustworthiness of CDSSs. Among others, counterfactual explanations prove to be one such XAI technique particularly suitable for the healthcare domain due to its ease of interpretation, even for less technically proficient staff.

A Randomized Controlled Trial on Automated Vehicle Technologies for Drivers With Parkinson's Disease.

Parkinson's disease (PD) negatively affects driver fitness. Few studies document the benefits of in-vehicle information systems (IVIS) and advanced-driver assistance systems (ADAS), the focus of this study, for drivers with PD. This study quantified the impact of IVIS and ADAS on the number of on-road driving errors.