Results 221 to 230 of about 56,688 (306)
Heuristic multi-site optimization for protein sequence design using Masked Protein Language Models. [PDF]
Wang L +5 more
europepmc +1 more source
Comparative study of ACO, dijkstra, and NN for routing efficiency in waste collection networks. [PDF]
Anitha R, Parthiban A.
europepmc +1 more source
Detecting cryptic ghost lineage introgression in four‐taxon genomic datasets
Abstract Premise Hybridization and introgression are pervasive evolutionary forces that have played fundamental roles in shaping the diversity of wild and domesticated plants. Four‐taxon tests for introgression provide a reliable framework for detecting signatures of ancient introgression from genomic data, which have played an important role in ...
Evan S. Forsythe +3 more
wiley +1 more source
Developing critical thinking through scaffolded peer feedback: an action research on heuristic design. [PDF]
Chen X.
europepmc +1 more source
ABSTRACT This study presents a multi‐method non‐invasive investigation of an approximately 4‐ha area associated with the long‐occupied coastal settlement of Rocavecchia (Apulia, southern Italy), situated between the prehistoric fortified peninsula and the Hellenistic‐Messapian walls.
Giuseppe Guarino +3 more
wiley +1 more source
Optimized inverse kinematics solutions for a 6-DOF robot. [PDF]
Bayoume MO +3 more
europepmc +1 more source
Abstract Artificial intelligence and large language models have significantly influenced medical education by enhancing learning experiences. While previous studies have assessed ChatGPT's performance on anatomy‐related questions, a notable gap remains in understanding its accuracy over time. This longitudinal study evaluated the progression of ChatGPT'
Bahattin Paslı, Ceren Günenç Beşer
wiley +1 more source
The Role of Rating Valence in AI Skin Cancer App Acceptance: Eye-Tracking and Questionnaire Study. [PDF]
Jagemann I, Hegner S, Hirschfeld G.
europepmc +1 more source
Students' perspectives on the use of social media in anatomy medical education: A survey study
Abstract Medical students are increasingly engaging with digital technologies for anatomy learning. However, investigations of students' perceptions of anatomy social media content are lacking. This study aims to explore medical students' perspectives of anatomy social media content and its self‐reported value as a learning resource.
Grace Powderly +5 more
wiley +1 more source

