SPE-YOLO: A deep learning model focusing on small pulmonary embolism detection.

Objectives: By developing the deep learning model SPE-YOLO, the detection of small pulmonary embolism has been improved, leading to more accurate identification of this condition. This advancement aims to better serve medical diagnosis and treatment.

Methods: This retrospective study analyzed images of 142 patients from Tianjin Medical University General Hospital using YOLOv8 as the foundational framework.

Improved Thermal Stability and Enhanced Thermoelectric Properties of p-Type BaCuTe by Doping of Cl.

Doping in semiconductors is a widely implemented strategy for manipulation of carrier concentration, which is a critical parameter to regulate the thermoelectric performance. Stoichiometric BaCuTe shows high hole concentration and unstable transport properties owing to the inherent Cu vacancy and dynamic precipitation behavior. In this work, Te has been partially substituted by Cl in BaCuTe to suppress the overhigh hole concentration.