Assistive Navigation Using Deep Reinforcement Learning Guiding Robot With UWB/Voice Beacons and Semantic Feedbacks for Blind and Visually Impaired People.

Facilitating navigation in pedestrian environments is critical for enabling people who are blind and visually impaired (BVI) to achieve independent mobility. A deep reinforcement learning (DRL)-based assistive guiding robot with ultrawide-bandwidth (UWB) beacons that can navigate through routes with designated waypoints was designed in this study. Typically, a simultaneous localization and mapping (SLAM) framework is used to estimate the robot pose and navigational goal; however, SLAM frameworks are vulnerable in certain dynamic environments.

Cramping, crashing, cannulating, and clotting: a qualitative study of patients' definitions of a "bad run" on hemodialysis.

Background: Hemodialysis sessions frequently become unstable from complications such as intradialytic hypotension and untoward symptoms. Previous patient safety initiatives promote prevention of treatment complications; yet, they have placed little specific focus on avoidable session instability. A patient-centered definition of session instability grounded in patient experiences, and an understanding of patient perceptions of causes and solutions to instability, may enable such efforts.

Lysine-specific molecular tweezers are broad-spectrum inhibitors of assembly and toxicity of amyloid proteins.

Amyloidoses are diseases characterized by abnormal protein folding and self-assembly, for which no cure is available. Inhibition or modulation of abnormal protein self-assembly, therefore, is an attractive strategy for prevention and treatment of amyloidoses. We examined Lys-specific molecular tweezers and discovered a lead compound termed CLR01, which is capable of inhibiting the aggregation and toxicity of multiple amyloidogenic proteins by binding to Lys residues and disrupting hydrophobic and electrostatic interactions important for nucleation, oligomerization, and fibril elongation.