Breakthrough in ultra-thin lithium metal anodes opens the era of longer-lasting batteries
Peer-Reviewed Publication
Updates every hour. Last Updated: 28-Apr-2025 01:08 ET (28-Apr-2025 05:08 GMT/UTC)
- Professor Yu Jong-sung’s team at DGIST, in collaboration with Pusan National University, develops a technology to enhance the stability of ultra-thin lithium metal anodes
Scientists developed a new way of investing in stocks using natural language processing. Using dynamic topic modeling, a variant of Latent Dirichlet Allocation, the new model uncovers hidden risk factors directly from company reports and translates them into tradable indices with minimal human oversight. Investors can now trade these risk factors directly and track industry trends using only the information contained in words.
Traditional terahertz (THz) polarization conversion devices show the unchanged polarization state on each output plane along the propagation path. This paper proposes a THz polarization controlled metasurface device that is dependent on propagation distance, which can continuously modify the polarization state of each output plane along the propagation path. The designed metasurface device can control the phase difference between the left-handed and right-handed circularly polarized components in the incident THz linearly polarized wave. This phase difference changes with the propagation distance, and ultimately outputs a linearly polarized wave that rotates along the propagation path. The polarization rotation angle can cover 0 to π. This device may have potential applications in fields such as variable matter excitation, THz communication, THz radar, THz sensing.
This work developed a new deep learning framework, MULGONET, to predict cancer recurrence and identify key biomarkers by integrating multi omics data (such as mRNA, DNA methylation, copy number variation). By utilizing the gene ontology (go) hierarchy, the model overcomes the challenges of data dimensionality and interpretability, and achieves higher accuracy in bladder cancer, pancreatic cancer, and gastric cancer datasets. This innovation enables clinicians to pinpoint key genes and biological pathways associated with cancer recurrence, paving the way for personalized treatment strategies.