Data management plan for the grant, "Collaborative Research: SHF: Small: LEGAS: Learning Evolving Graphs At Scale." This project aims to improve the computation efficiency of graph neural networks (GNNs), which are an emerging class of deep learning models on graphs, with many successful applications, such as, recommendation systems, drug discovery, social network analysis, and code vulnerability detection. This project aims to to design an efficient GNN framework via algorithm and system co-design for both static and dynamic graphs.

Data management plan for the grant, "Collaborative Research: DMREF: AI-enabled Automated design of ultrastrong and ultraelastic metallic alloys"

Data management plan for the grant, "Collaborative Research: IRES Track I: Wireless Federated Fog Computing for Remote Industry 4.0 Applications."

Article states that although KRASG12C inhibitors have shown promising activity in lung adenocarcinomas harboring KRASG12C, acquired resistance to these therapies eventually occurs in most patients. The authors report that the hedgehog signal is induced by KRASG12C inhibitors and mediates KRAS re-expression in cancer cells treated with a KRASG12C inhibitor.

Article describes how blending of ceramic constituent phases enhances sinterability and performance in high strength ceramics. The authors describe how a near fully dense blended boron carbide (B4C)-titanium diboride (TiB2) composite produced through spark plasma sintering (SPS) is probed to understand the mechanical performance under dynamic uniaxial strain, or shock compression.

Data management plan for the grant, "Collaborative Research: Topological Defects and Dynamic Motion of Symmetry-breaking Tadpole Particles in Liquid Crystal Medium."